Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-13T02:39:29.411021Z
Paper Citation Record · LEDGER
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
As of 7 August 2026, this Paper Citation Record lists 100 of 109 outbound references and 100 inbound Pith citation observations for arXiv:2104.13478.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T06:01:37.731916Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T02:28:24.338817Z
Reference resolution
100 of 109 outbound references displayed
- verified exact92
- verified fuzzy2
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch6
External citation measurements
557
pith, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 3e408275-a5bd-41a2-9c38-62d882b4fbbb · outbound
This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges On the Bottleneck of Graph Neural Networks and its Practical Implications
Reference 1
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.946606Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0504efcc-346f-420d-892e-051ffc15f118 · outbound
This paper cites Cormorant: Covariant Molecular Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Cormorant: Covariant Molecular Neural Networks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.466252Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 04865216-f598-46b8-8b7c-e9d4fc416ba7 · outbound
This paper cites Layer Normalization.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Layer Normalization
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.473522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f1c471d0-0e09-4c16-ad2c-a7cb3b84b3ac · outbound
This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Machine Translation by Jointly Learning to Align and Translate
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.479619Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ab95a0ea-54d1-4b0d-91fb-894be7620fb8 · outbound
This paper cites Discovering Transforms: A Tutorial on Circulant Matrices, Circular Convolution, and the Discrete Fourier Transform.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Discovering Transforms: A Tutorial on Circulant Matrices, Circular Convolution, and the Discrete Fourier Transform
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.486592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a2e03a7e-68b6-4ee6-be68-32cdb19d3233 · outbound
This paper cites Interaction Networks for Learning about Objects, Relations and Physics.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Interaction Networks for Learning about Objects, Relations and Physics
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.493879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b41a7c84-7c6e-4d7d-bde4-5655d7b1bd93 · outbound
This paper cites Relational inductive biases, deep learning, and graph networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Relational inductive biases, deep learning, and graph networks
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.499611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a462cf1a-5268-4ee2-9bf9-add23076e726 · outbound
This paper cites Directional Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Directional Graph Networks
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.505818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 032aea1f-94bb-4a07-b919-73df74993fc2 · outbound
This paper cites Size-Invariant Graph Representations for Graph Classification Extrapolations.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Size-Invariant Graph Representations for Graph Classification Extrapolations
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.512443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 621c9de1-61ee-4660-bea0-2362b6adbbc5 · outbound
This paper cites Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:29.518586Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6d317395-31d6-4d19-aef0-a12e828e3f29 · outbound
This paper cites A Quadratic Assignment Formulation of the Graph Edit Distance.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges A Quadratic Assignment Formulation of the Graph Edit Distance
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T20:44:33.063278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b3acedb1-b9f6-4cc8-85ef-a4ff59b79141 · outbound
This paper cites Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.532705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ec42c474-1aff-40f4-8d11-68be4fb77943 · outbound
This paper cites Language Models are Few-Shot Learners.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Language Models are Few-Shot Learners
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.538219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 490de120-0674-4396-a3fa-9bf89ab1ba42 · outbound
This paper cites Combinatorial optimization and reasoning with graph neural networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Combinatorial optimization and reasoning with graph neural networks
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.545618Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 063aa4b8-eb87-40e2-9073-251788c03d85 · outbound
This paper cites Neural Ordinary Differential Equations.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Ordinary Differential Equations
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T13:00:58.588645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a675dcbf-7643-4120-ad43-8ebb68ffa267 · outbound
This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.556641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fa0137be-5af9-4cea-8aad-6aca36ee6bf2 · outbound
This paper cites Spherical CNNs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Spherical CNNs
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.563287Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3b600e83-a675-45aa-90c9-6c2287592db9 · outbound
This paper cites Recurrent Batch Normalization.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Recurrent Batch Normalization
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.569422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8923969f-1465-4f21-9c82-3b7934f018bc · outbound
This paper cites Principal Neighbourhood Aggregation for Graph Nets.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Principal Neighbourhood Aggregation for Graph Nets
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.574637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 60b6f0c2-d989-42d4-b1e6-ff587c858824 · outbound
This paper cites Lagrangian Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Lagrangian Neural Networks
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.580545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5f81ed84-abae-4eb7-b757-1d874a3d0833 · outbound
This paper cites Learning Symbolic Physics with Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Symbolic Physics with Graph Networks
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.586442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 31bd933b-11c1-40a5-bc8c-773f82f4ad5d · outbound
This paper cites XLVIN: eXecuted Latent Value Iteration Nets.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges XLVIN: eXecuted Latent Value Iteration Nets
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.592955Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a536be96-a7c9-4383-a706-3c07e932cebe · outbound
This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.598720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2c776389-3049-4212-b19a-8771e7ad6ca0 · outbound
This paper cites A Generalization of Transformer Networks to Graphs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges A Generalization of Transformer Networks to Graphs
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.604405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d48613e7-3410-45d1-afb8-75f97771d37e · outbound
This paper cites Spin-Weighted Spherical CNNs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Spin-Weighted Spherical CNNs
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.610372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 635c9c05-ba51-47dc-b5be-2bc96b13071a · outbound
This paper cites Hierarchical Inter-Message Passing for Learning on Molecular Graphs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Hierarchical Inter-Message Passing for Learning on Molecular Graphs
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.616024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2c4bc1c8-e163-466f-97a3-894cf1c1191d · outbound
This paper cites Neural Shuffle-Exchange Networks -- Sequence Processing in O(n log n) Time.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Shuffle-Exchange Networks -- Sequence Processing in O(n log n) Time
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.621770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 964c9cbe-5d94-4ec3-9356-e2783753452c · outbound
This paper cites SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.627199Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4e6ece74-4771-4f7f-b34a-e3f0c5314ff7 · outbound
This paper cites Learning Graph Representations with Embedding Propagation.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Graph Representations with Embedding Propagation
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T22:15:25.236731Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0a36ea52-6f65-461e-9300-b74a57c51a8b · outbound
This paper cites Texture Synthesis Using Convolutional Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Texture Synthesis Using Convolutional Neural Networks
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.637263Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a1404f6b-22f3-42a7-9a39-c957ce6fff68 · outbound
This paper cites Neural Message Passing for Quantum Chemistry.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Message Passing for Quantum Chemistry
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.643649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a6f822aa-6602-4d0c-a9f9-7af258ba8c04 · outbound
This paper cites Generative Adversarial Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Generative Adversarial Networks
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T04:04:41.117563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 72f54db9-b73c-4f9e-86d3-303d3d612186 · outbound
This paper cites Generating Sequences With Recurrent Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Generating Sequences With Recurrent Neural Networks
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.653472Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7805e6a2-b8b2-4907-829f-a39052c199c2 · outbound
This paper cites Neural Turing Machines.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Turing Machines
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T07:34:44.411886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f11a2512-68fe-40f7-b646-59ee622a76cd · outbound
This paper cites Bootstrap your own latent: A new approach to self-supervised Learning.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Bootstrap your own latent: A new approach to self-supervised Learning
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.664197Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ce0a0a04-b0e2-4fb5-aae2-cd4dae08a25d · outbound
This paper cites Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Network Medicine Framework for Identifying Drug Repurposing Opportunities for COVID-19
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.668153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d5532446-9526-437a-a0a2-f9a03f6fe4cc · outbound
This paper cites Identity Matters in Deep Learning.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Identity Matters in Deep Learning
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.673718Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ec4453fd-5eda-4172-8158-d5ec1368a0c3 · outbound
This paper cites VAIN: Attentional Multi-agent Predictive Modeling.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges VAIN: Attentional Multi-agent Predictive Modeling
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T23:05:20.372525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9b4502b0-a02b-4b1f-8d83-957ec540a9de · outbound
This paper cites LieTransformer: Equivariant self-attention for Lie Groups.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges LieTransformer: Equivariant self-attention for Lie Groups
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.685633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6895bcaa-95c8-40bc-bbbf-63539d010ef8 · outbound
This paper cites Sarah Itani and Dorina Thanou.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Sarah Itani and Dorina Thanou
Reference 40
- Resolution
- verified exact
- doi, observed 2026-05-13T02:39:29.458632Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7fb2381d-9723-4af4-a4b8-7b08dd9b8844 · outbound
This paper cites Neural GPUs Learn Algorithms.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural GPUs Learn Algorithms
Reference 41
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.692653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 391dc76c-c6e4-4340-a1cb-1e16f1583c2d · outbound
This paper cites Neural Machine Translation in Linear Time.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Machine Translation in Linear Time
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.697503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7508d309-f1cd-43a3-bfa3-4186eeb918a8 · outbound
This paper cites Differentiable Graph Module (DGM) for Graph Convolutional Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Differentiable Graph Module (DGM) for Graph Convolutional Networks
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.701933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7bbb1a89-88d1-4e9f-bc3a-b1b41385ede9 · outbound
This paper cites Interpretable Stability Bounds for Spectral Graph Filters.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Interpretable Stability Bounds for Spectral Graph Filters
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.707631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 00ee9ca0-4b75-4c72-aebf-20d7cb82e2d0 · outbound
This paper cites Adam: A Method for Stochastic Optimization.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Adam: A Method for Stochastic Optimization
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.712952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0c9138e0-51fe-46e7-be73-fd9a658b2113 · outbound
This paper cites Auto-Encoding Variational Bayes.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Auto-Encoding Variational Bayes
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.719225Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2d0ad842-13fb-4874-810a-b1894ef00480 · outbound
This paper cites Semi-Supervised Classification with Graph Convolutional Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Semi-Supervised Classification with Graph Convolutional Networks
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.724979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dafc8e78-9b1b-4531-a67c-761d4b647dcf · outbound
This paper cites Directional Message Passing for Molecular Graphs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Directional Message Passing for Molecular Graphs
Reference 48
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:29.731944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 233f2425-3920-4538-88d5-cd9cef880bdb · outbound
This paper cites Energyflownetworks: deep sets for particle jets.Journal of High Energy Physics, 2019(1):121.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Energyflownetworks: deep sets for particle jets.Journal of High Energy Physics, 2019(1):121
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T02:39:30.061772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ed00320e-cfd8-4b20-876c-bdf0f7de4035 · outbound
This paper cites Neural Random-Access Machines.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Random-Access Machines
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.762364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 18593e1c-5bbe-4f05-91c9-483383bf4598 · outbound
This paper cites Gated Graph Sequence Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Gated Graph Sequence Neural Networks
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.767720Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d4860152-e58a-4513-900f-c82c7a65386c · outbound
This paper cites Neural Arithmetic Units.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Arithmetic Units
Reference 52
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.772640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0cd8efb9-8a8c-4f3e-bb78-772c3f3e053a · outbound
This paper cites 3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges 3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.778346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 778f4061-beb5-4b92-8b90-eba105f805ef · outbound
This paper cites Learning Representations of Missing Data for Predicting Patient Outcomes.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Representations of Missing Data for Predicting Patient Outcomes
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T23:11:31.123994Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9253f483-53c4-42bc-b261-6a16a93508ae · outbound
This paper cites Invariant and Equivariant Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Invariant and Equivariant Graph Networks
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.790768Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0bda428a-6455-4ca3-acc5-81cb62b22d4e · outbound
This paper cites Provably Powerful Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Provably Powerful Graph Networks
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.796072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 464acd0a-718b-4987-8b52-ab6e4d0d00bb · outbound
This paper cites Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.801867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f7c4c616-6167-4781-a4d8-ea06591d88c1 · outbound
This paper cites Learning with invariances in random features and kernel models.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning with invariances in random features and kernel models
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.807578Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4bebcdae-307c-485b-9d2d-8d399fce1d31 · outbound
This paper cites Representation Learning via Invariant Causal Mechanisms.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Representation Learning via Invariant Causal Mechanisms
Reference 59
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:29.814678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c7bd61a2-83e5-4b81-bc0c-c348fb21363c · outbound
This paper cites Fake News Detection on Social Media using Geometric Deep Learning.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Fake News Detection on Social Media using Geometric Deep Learning
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.820067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e1460dfd-7075-4689-9fb0-4a20c89afbfd · outbound
This paper cites Loopy Belief Propagation for Approximate Inference: An Empirical Study.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Loopy Belief Propagation for Approximate Inference: An Empirical Study
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.825784Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d85b1a15-8c72-488e-bd3b-f5c3ec0e0045 · outbound
This paper cites Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Janossy Pooling: Learning Deep Permutation-Invariant Functions for Variable-Size Inputs
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.831241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b015a592-101a-45cf-b688-875bb01ead1c · outbound
This paper cites Fourier-based and Rational Graph Filters for Spectral Processing.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Fourier-based and Rational Graph Filters for Spectral Processing
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.837144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 39ad2c8a-692c-4677-b52c-5619770e6394 · outbound
This paper cites Learning Mesh-Based Simulation with Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Learning Mesh-Based Simulation with Graph Networks
Reference 64
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:29.843294Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7332857b-a5ee-4368-9488-65b97cac7fb2 · outbound
This paper cites ParticleNet: Jet Tagging via Particle Clouds.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges ParticleNet: Jet Tagging via Particle Clouds
Reference 65
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:29.848931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 45d74684-3cb4-4576-baa3-fb87e1bfaf6a · outbound
This paper cites Implicit Regularization in Deep Learning May Not Be Explainable by Norms.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Implicit Regularization in Deep Learning May Not Be Explainable by Norms
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.853910Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 347b8269-b9e3-46a1-ab02-e6555c6d2d3c · outbound
This paper cites Neural Programmer-Interpreters.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Programmer-Interpreters
Reference 67
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.859302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8a76c11b-09d3-4059-8c8f-aacb4a59a1c7 · outbound
This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Reference 68
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.864759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f0361a35-6ceb-49d9-98e3-7a4bbb751432 · outbound
This paper cites Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Temporal Pointwise Convolutional Networks for Length of Stay Prediction in the Intensive Care Unit
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.870770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7444259e-7b87-4d95-97e6-acdb9f629a1e · outbound
This paper cites Predicting Patient Outcomes with Graph Representation Learning.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Predicting Patient Outcomes with Graph Representation Learning
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.875611Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a352b1ee-a935-4c28-92a1-b1f6860a3411 · outbound
This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Temporal Graph Networks for Deep Learning on Dynamic Graphs
Reference 71
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T17:04:50.770517Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ba716125-2f9e-455d-ae31-2369fd407334 · outbound
This paper cites Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.886304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 7b33e56a-d685-4574-9283-e012356e0a6c · outbound
This paper cites Hamiltonian Graph Networks with ODE Integrators.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Hamiltonian Graph Networks with ODE Integrators
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.890639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 674dfcce-6126-4394-a53d-5e140ed815ff · outbound
This paper cites Relational recurrent neural networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Relational recurrent neural networks
Reference 74
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T22:52:26.002627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f4da9815-b064-4ef7-977f-ffb5bbb30d29 · outbound
This paper cites How Does Batch Normalization Help Optimization?.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges How Does Batch Normalization Help Optimization?
Reference 75
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.901228Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d567c2b2-f916-41be-b8a4-b8a3f9623145 · outbound
This paper cites Random Features Strengthen Graph Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Random Features Strengthen Graph Neural Networks
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.906377Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation dad289a8-7cc0-4e94-aa53-c4b458e8d10e · outbound
This paper cites E(n) Equivariant Graph Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges E(n) Equivariant Graph Neural Networks
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.913190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 90994c2a-a4d4-48e2-b1d3-c8b6862a986e · outbound
This paper cites Proximal Policy Optimization Algorithms.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Proximal Policy Optimization Algorithms
Reference 78
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.919102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 195952c7-c289-4141-a075-d46aa9a11efd · outbound
This paper cites Implicit Regularization in ReLU Networks with the Square Loss.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Implicit Regularization in ReLU Networks with the Square Loss
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.924598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 32e1a959-440d-4701-b826-25b590c5824d · outbound
This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Very Deep Convolutional Networks for Large-Scale Image Recognition
Reference 80
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:29.929432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 93ee2a75-54c8-4d91-9750-350fe2df77fa · outbound
This paper cites Hierarchical Protein Function Prediction with Tail-GNNs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Hierarchical Protein Function Prediction with Tail-GNNs
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.935744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ae8824ce-076f-4500-80d6-7212dd52102a · outbound
This paper cites Striving for Simplicity: The All Convolutional Net.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Striving for Simplicity: The All Convolutional Net
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.940934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 84b7b873-fb61-431d-b38d-2e1e2c683f59 · outbound
This paper cites On the Equivalence between Positional Node Embeddings and Structural Graph Representations.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges On the Equivalence between Positional Node Embeddings and Structural Graph Representations
Reference 83
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.738029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c64d943a-1c5c-4834-b5d4-876223cdb87f · outbound
This paper cites Dropout: a simple way to prevent neural networks from overfitting.JMLR, 15(1):1929–1958.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Dropout: a simple way to prevent neural networks from overfitting.JMLR, 15(1):1929–1958
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-13T02:39:30.065798Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e90f5fb9-429f-451e-a8f8-3ce0b0eb4d8f · outbound
This paper cites Highway Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Highway Networks
Reference 85
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.951918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation fb4bc555-1b02-4574-a02b-7233413fb070 · outbound
This paper cites Graph Networks with Spectral Message Passing.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Graph Networks with Spectral Message Passing
Reference 86
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.958339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 061858e7-6d1d-48ea-93ac-e0d680b51fc3 · outbound
This paper cites Persistent Message Passing.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Persistent Message Passing
Reference 87
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.963203Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6e16d5e8-c021-43d3-8601-076891c27be3 · outbound
This paper cites Early History of Gauge Theories and Weak Interactions.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Early History of Gauge Theories and Weak Interactions
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:07:47.064421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c0130c1a-1b19-482e-8ca3-925164c3bc64 · outbound
This paper cites Sequence to Sequence Learning with Neural Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Sequence to Sequence Learning with Neural Networks
Reference 89
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.973069Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 273a82de-9cbd-4e7c-bbb0-8e2ba747da0d · outbound
This paper cites Can recurrent neural networks warp time?.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Can recurrent neural networks warp time?
Reference 90
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.977924Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4b940852-f563-4bf2-b58f-6bfdb295638b · outbound
This paper cites Large-Scale Representation Learning on Graphs via Bootstrapping.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Large-Scale Representation Learning on Graphs via Bootstrapping
Reference 91
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.983736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 41d5513f-2cad-4977-83ff-051d56078f73 · outbound
This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds
Reference 92
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.989691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a73ffd11-4081-4b1b-9b54-ae55b6c7a61c · outbound
This paper cites Neural Arithmetic Logic Units.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Arithmetic Logic Units
Reference 93
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.994500Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 179172a4-2dd9-4711-a038-074dbeca22e7 · outbound
This paper cites Instance Normalization: The Missing Ingredient for Fast Stylization.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Instance Normalization: The Missing Ingredient for Fast Stylization
Reference 94
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:29.999105Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c555b75f-c5a6-4e17-b92f-9198820fa97b · outbound
This paper cites WaveNet: A Generative Model for Raw Audio.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges WaveNet: A Generative Model for Raw Audio
Reference 95
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T02:39:30.003876Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6e04143f-deb2-4990-983c-bb8f4e9f40eb · outbound
This paper cites Neural Execution of Graph Algorithms.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Neural Execution of Graph Algorithms
Reference 96
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.008473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d6d79832-64ef-40fb-821e-96faf68e6c27 · outbound
This paper cites Pointer Graph Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Pointer Graph Networks
Reference 97
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.013963Z
Source-reported events for the cited work
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Observation b583d060-abe3-4a5e-9872-4837fc4217f3 · outbound
This paper cites Pointer Networks.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Pointer Networks
Reference 98
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 97f2d565-ae94-4904-9582-8880992bf811 · outbound
This paper cites 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges 3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data
Reference 99
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9982274f-930a-436c-a6aa-56cf9a33babc · outbound
This paper cites Inductive Representation Learning on Temporal Graphs.
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges Inductive Representation Learning on Temporal Graphs
Reference 100
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Pith citing papers
Observation faf9ba21-5246-47f0-98ee-67c041e532db · inbound
Graph State-Space Models and Latent Relational Inference cites this paper.
Graph State-Space Models and Latent Relational Inference Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9f99c405-fbef-4a4c-9a41-c34139e383b8 · inbound
Complete invariants of atomic clouds under rigid motion with Lipschitz continuous metrics in a polynomial time cites this paper.
Complete invariants of atomic clouds under rigid motion with Lipschitz continuous metrics in a polynomial time Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 11
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0c657333-c417-484d-ac96-250f846e1ef2 · inbound
Massive Activations in Large Language Models cites this paper.
Massive Activations in Large Language Models Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5603653e-240b-4e79-a89a-10d7fa39abb9 · inbound
Quantum Convolutional Neural Networks are Effectively Classically Simulable cites this paper.
Quantum Convolutional Neural Networks are Effectively Classically Simulable Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 11
- Resolution
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- local_arxiv, observed 2026-05-23T22:05:49.983700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 852b569d-e9af-4e64-bbaa-9b10bf3f0ba4 · inbound
Resource-efficient equivariant quantum convolutional neural networks cites this paper.
Resource-efficient equivariant quantum convolutional neural networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4c774b76-6d89-4d0d-a4a6-64f5de412e52 · inbound
Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing cites this paper.
Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2022
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 170fe615-c194-4229-a6f7-cda2f8bd827d · inbound
HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals cites this paper.
HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b730ed99-a377-4a9f-9086-f6a129325da9 · inbound
HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals cites this paper.
HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 18e57f7b-5bb5-4f61-aa7b-9cac3a344ace · inbound
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning cites this paper.
Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 11
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- unresolved
- no resolver link, observed 2026-08-07T04:19:37.692994Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f3f7220-d772-40fd-ab44-78e85b0f72a0 · inbound
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork cites this paper.
Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 17
- Resolution
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- no resolver link, observed 2026-08-07T04:21:11.063478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85e0d42d-0697-4493-bdfb-ec01f7b96aa3 · inbound
Quantum-Inspired Differentiable Integral Neural Networks (QIDINNs): A Feynman-Based Architecture for Continuous Learning Over Streaming Data cites this paper.
Quantum-Inspired Differentiable Integral Neural Networks (QIDINNs): A Feynman-Based Architecture for Continuous Learning Over Streaming Data Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 9
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- no resolver link, observed 2026-08-07T04:09:40.311234Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e996621d-9060-44a0-9b37-4df90f489847 · inbound
Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach cites this paper.
Uncertainty-Aware Graph Neural Networks: A Multi-Hop Evidence Fusion Approach Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
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- no resolver link, observed 2026-08-07T00:42:11.009350Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4211aa2b-53e1-41a4-bdb7-d21c2edfb31c · inbound
CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization cites this paper.
CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 16
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- unresolved
- no resolver link, observed 2026-08-06T23:48:23.944511Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 628eb03b-b7af-4c8e-873f-2c741e6e8009 · inbound
Robot Tactile Gesture Recognition Based on Full-body Modular E-skin cites this paper.
Robot Tactile Gesture Recognition Based on Full-body Modular E-skin Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:28:14.717604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5201ba91-9cb7-474f-a80a-9076e95882d2 · inbound
On Equivariant Model Selection through the Lens of Uncertainty cites this paper.
On Equivariant Model Selection through the Lens of Uncertainty Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 10
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- unresolved
- no resolver link, observed 2026-08-06T23:21:45.289074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1495cc61-5674-4986-adf4-77ea34aafa99 · inbound
Ontology Neural Network and ORTSF: A Framework for Topological Reasoning and Delay-Robust Control cites this paper.
Ontology Neural Network and ORTSF: A Framework for Topological Reasoning and Delay-Robust Control Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 37
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- no resolver link, observed 2026-08-06T23:12:53.995047Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 354bf1a5-03c5-4da0-b01f-ade6bd86e61c · inbound
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning cites this paper.
Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
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- no resolver link, observed 2026-08-06T23:11:55.740635Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6f3c9def-ff90-47de-9fad-d5951972d1b6 · inbound
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules cites this paper.
DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 14
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- unresolved
- no resolver link, observed 2026-08-07T05:14:41.159626Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23ffeffa-0182-4e89-9201-be53b9a30349 · inbound
Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence cites this paper.
Beyond Statistical Learning: Exact Learning Is Essential for General Intelligence Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2003
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 946ff248-9171-4296-a375-fc08f3b04a29 · inbound
Reinforcement Learning for Automated Cybersecurity Penetration Testing cites this paper.
Reinforcement Learning for Automated Cybersecurity Penetration Testing Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
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- no resolver link, observed 2026-08-06T21:31:51.228923Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 628e6186-7d9a-4200-8038-857aff438fe2 · inbound
Relational inductive biases on attention mechanisms cites this paper.
Relational inductive biases on attention mechanisms Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 6
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 267b6a77-0c3b-4c8d-a75e-689e4f62e8ea · inbound
Sinkhorn Normalization of Diffusion Kernels cites this paper.
Sinkhorn Normalization of Diffusion Kernels Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2010
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- no resolver link, observed 2026-08-06T19:19:49.127763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c647d235-7baa-48ce-aac0-5ab6438f33c3 · inbound
Filter Equivariant Functions: A symmetric account of length-general extrapolation on lists cites this paper.
Filter Equivariant Functions: A symmetric account of length-general extrapolation on lists Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fad51347-cdc0-4689-a99e-78e82893a341 · inbound
Do we need equivariant models for molecule generation? cites this paper.
Do we need equivariant models for molecule generation? Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 60700348-67c0-43cb-ad23-5c77db928844 · inbound
Polaritonic Machine Learning for Graph-based Data Analysis cites this paper.
Polaritonic Machine Learning for Graph-based Data Analysis Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 11
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- no resolver link, observed 2026-08-06T17:40:15.358153Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62cc3016-743a-4ae8-8bf5-5c6c28de802b · inbound
Tensor-Tensor Products, Group Representations, and Semidefinite Programming cites this paper.
Tensor-Tensor Products, Group Representations, and Semidefinite Programming Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2025
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99e8ec6c-5ed1-4aef-a009-bc8c81cd9f5f · inbound
Localized FNO for Spatiotemporal Hemodynamic Upsampling in Aneurysm MRI cites this paper.
Localized FNO for Spatiotemporal Hemodynamic Upsampling in Aneurysm MRI Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 125c57de-5655-458b-b898-7ce20676ec09 · inbound
PyG 2.0: Scalable Learning on Real World Graphs cites this paper.
PyG 2.0: Scalable Learning on Real World Graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 10
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f225f0ef-9da6-407f-b853-e5f7e2a69bb7 · inbound
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces cites this paper.
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 17
- Resolution
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- no resolver link, observed 2026-08-06T13:21:58.969867Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff4c5e77-0556-4876-bc56-0f4feba65d0d · inbound
Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning cites this paper.
Hierarchical Message-Passing Policies for Multi-Agent Reinforcement Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 17
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7135985-177d-454f-9997-0c3399b2824d · inbound
TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows cites this paper.
TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 13
- Resolution
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- no resolver link, observed 2026-08-05T23:39:46.038724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce389129-4d3f-42f3-ac03-85db5c4b5e02 · inbound
Exact Verification of Graph Neural Networks with Incremental Constraint Solving cites this paper.
Exact Verification of Graph Neural Networks with Incremental Constraint Solving Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 3
- Resolution
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- local_arxiv, observed 2026-05-18T23:01:54.706291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation ccf2ac0d-9a21-4cfc-8351-e711b6e025b2 · inbound
Deep Learning in Classical and Quantum Physics cites this paper.
Deep Learning in Classical and Quantum Physics Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 100
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a10cac8d-a2e6-4220-8c61-4f1850f641a3 · inbound
Attention Mechanism in Randomized Time Warping cites this paper.
Attention Mechanism in Randomized Time Warping Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 9
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 69e6de8f-f90d-48ef-9c7a-4004e04674e8 · inbound
Memorization in Graph Neural Networks cites this paper.
Memorization in Graph Neural Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 14
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31b0f3bb-68dc-478b-a1a6-7f52e1520b22 · inbound
A gauge theory of complex adaptive systems cites this paper.
A gauge theory of complex adaptive systems Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 43
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c628aa9d-dec6-4394-a61b-d69bbd0d1b2c · inbound
On sources to variabilities of simple cells in the primary visual cortex: A principled theory for the interaction between geometric image transformations and receptive field responses cites this paper.
On sources to variabilities of simple cells in the primary visual cortex: A principled theory for the interaction between geometric image transformations and receptive field responses Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T20:21:50.278800Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c6c10c5a-5418-4f43-b1c1-a67a664acf98 · inbound
Universal Representation of Generalized Convex Functions and their Gradients cites this paper.
Universal Representation of Generalized Convex Functions and their Gradients Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:36:48.103018Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 37eba6a7-6ba0-4db6-8e66-2beb884e4077 · inbound
Data-driven discovery of dynamical models in biology cites this paper.
Data-driven discovery of dynamical models in biology Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 204
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 62489fa9-e7da-4349-a648-0dd7b73f442e · inbound
Learning from one graph: transductive learning guarantees via the geometry of small random worlds cites this paper.
Learning from one graph: transductive learning guarantees via the geometry of small random worlds Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 9
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 59fb7154-22df-4b65-b1c5-964a4016313d · inbound
Learning words in groups: fusion algebras, tensor ranks and grokking cites this paper.
Learning words in groups: fusion algebras, tensor ranks and grokking Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
- Resolution
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- no resolver link, observed 2026-08-04T22:57:12.064758Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7639421b-6fb3-4f44-a869-4271bf6a6d05 · inbound
Contextuality, Holonomy and Discrete Fiber Bundles in Group-Valued Boltzmann Machines cites this paper.
Contextuality, Holonomy and Discrete Fiber Bundles in Group-Valued Boltzmann Machines Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:40:15.352379Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e5d9afda-9dd8-4ee7-ba6b-ca6ea5af3787 · inbound
Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later cites this paper.
Geometric Autoencoder Priors for Bayesian Inversion: Learn First Observe Later Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T14:26:28.460526Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c3308337-8cff-4de2-880d-279d7f0d457e · inbound
Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks cites this paper.
Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T12:46:23.318899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 0ccbfde5-29ec-45bd-9231-1886d52d3cb1 · inbound
AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration cites this paper.
AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T21:50:41.241660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 34d4de88-d8af-405d-aba9-84469e6309f6 · inbound
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks cites this paper.
VDW-GNNs: Vector diffusion wavelets for geometric graph neural networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2017
- Resolution
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- no resolver link, observed 2026-08-04T13:23:57.820410Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8378a77c-029c-42ea-819d-3e776ed113b8 · inbound
The Principle of Isomorphism: A Theory of Population Activity in Grid Cells and Beyond cites this paper.
The Principle of Isomorphism: A Theory of Population Activity in Grid Cells and Beyond Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T12:44:51.105889Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ffbeecd3-27f7-4096-bfd2-8a4de8067b46 · inbound
Platonic Transformers: A Solid Choice For Equivariance cites this paper.
Platonic Transformers: A Solid Choice For Equivariance Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T12:27:30.706433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 711a71e6-4c37-4127-b36b-4f814dbba8a6 · inbound
Conditional Clifford-Steerable CNNs for PDE Modeling cites this paper.
Conditional Clifford-Steerable CNNs for PDE Modeling Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 6
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3338cb4-4517-4e96-8921-2b96dbe54ccc · inbound
On Universality of Deep Equivariant Networks cites this paper.
On Universality of Deep Equivariant Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 297f743f-d546-4eb7-ae86-6bd6d2e5fac7 · inbound
Control Synthesis with Reinforcement Learning: A Modeling Perspective cites this paper.
Control Synthesis with Reinforcement Learning: A Modeling Perspective Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b64530dd-623f-4dd4-9782-0cdd6ca71cc6 · inbound
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models cites this paper.
Scalable Single-Cell Gene Expression Generation with Latent Diffusion Models Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 26
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f2bc13a-bae9-47fa-8d49-08add318fa65 · inbound
Twirlator: A Pipeline for Analyzing Subgroup Symmetry Effects in Quantum Machine Learning Ansatzes cites this paper.
Twirlator: A Pipeline for Analyzing Subgroup Symmetry Effects in Quantum Machine Learning Ansatzes Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ecd7df78-6db6-4f7a-84c8-c404d1ae282c · inbound
Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners cites this paper.
Lost in Serialization: Invariance and Generalization of LLM Graph Reasoners Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2021
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf59985f-422c-4b51-b947-438c033834c3 · inbound
Warm-starting active-set solvers using graph neural networks cites this paper.
Warm-starting active-set solvers using graph neural networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4392afad-f92b-40a5-a076-5fcf2c97870c · inbound
Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power cites this paper.
Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
- Resolution
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- local_arxiv, observed 2026-05-21T17:50:26.279166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation aae7a062-b74e-4107-8dd9-9c4f398383a9 · inbound
Generalized Spherical Neural Operators: Green's Function Formulation cites this paper.
Generalized Spherical Neural Operators: Green's Function Formulation Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T23:08:40.052848Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6f1dfcac-80de-48e9-863f-b19eefcea059 · inbound
Torch Geometric Pool: the PyTorch library for pooling in Graph Neural Networks cites this paper.
Torch Geometric Pool: the PyTorch library for pooling in Graph Neural Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T22:48:38.134247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 963bf073-5b30-429e-9db1-1fea9acea1f0 · inbound
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework cites this paper.
Bridging Data and Physics: A Graph Neural Network-Based Hybrid Twin Framework Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 6
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d60f99ef-01a7-4ce8-bbe4-86a3edfaaf00 · inbound
AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes cites this paper.
AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T17:51:08.939215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9f09009a-6dc2-4887-85b0-1f4da4a66309 · inbound
AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes cites this paper.
AI-enhanced tuning of quantum dot Hamiltonians toward Majorana modes Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 47
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- no resolver link, observed 2026-08-03T12:41:08.973415Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33e2c624-619a-44c8-9db2-05f56b68eb59 · inbound
Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels cites this paper.
Attention in Geometry: Scalable Spatial Modeling via Adaptive Density Fields and FAISS-Accelerated Kernels Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 7
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- no resolver link, observed 2026-08-03T12:48:17.748297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e594131c-8a2a-4fb5-b0f6-6e6336a18649 · inbound
Latent Dynamics Graph Convolutional Networks for model order reduction of parameterized time-dependent PDEs cites this paper.
Latent Dynamics Graph Convolutional Networks for model order reduction of parameterized time-dependent PDEs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:12:36.930070Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85eae15d-617c-4498-aad0-eb24ff6259eb · inbound
Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning cites this paper.
Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T10:04:25.857442Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27bc6df4-6f9c-4472-97a2-1da6a44ec40f · inbound
VENI: Variational Encoder for Natural Illumination cites this paper.
VENI: Variational Encoder for Natural Illumination Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T09:26:16.591384Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22c30033-4756-41f9-aeab-3471911dde10 · inbound
Identifiable Equivariant Networks are Layerwise Equivariant cites this paper.
Identifiable Equivariant Networks are Layerwise Equivariant Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2025
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d24d779-24df-412d-9952-78a5cbfaea71 · inbound
On the Expressive Power of Permutation-Equivariant Weight-Space Networks cites this paper.
On the Expressive Power of Permutation-Equivariant Weight-Space Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:57:05.890983Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a87cab2-d130-4aeb-bb8d-ab34a27c7f28 · inbound
Inverting Data Transformations via Diffusion Sampling cites this paper.
Inverting Data Transformations via Diffusion Sampling Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2256
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e04b929-e2ee-49f3-885e-152077d3d5cb · inbound
Descriptive power and predictive limits of a discrete Hasimoto--DNLS model of protein backbone structure cites this paper.
Descriptive power and predictive limits of a discrete Hasimoto--DNLS model of protein backbone structure Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:39:55.011053Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation deb19ca4-8d26-4f8e-959c-3333a39c036d · inbound
Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps cites this paper.
Geodesic Semantic Search: Cartographic Navigation of Citation Graphs with Learned Local Riemannian Maps Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T20:20:19.908840Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 360e1221-4a1a-476c-b886-e5702fdece49 · inbound
Polarized Target Nuclear Magnetic Resonance Measurements with Deep Neural Networks cites this paper.
Polarized Target Nuclear Magnetic Resonance Measurements with Deep Neural Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T12:50:00.370146Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8ab958fd-0a64-48e7-9595-2ff20fa661c3 · inbound
Spectral methods: crucial for machine learning, natural for quantum computers? cites this paper.
Spectral methods: crucial for machine learning, natural for quantum computers? Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 39
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T00:23:22.316151Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a6fed213-c955-4dd8-b93e-1a4ee694998f · inbound
Metriplector: From Field Theory to Neural Architecture cites this paper.
Metriplector: From Field Theory to Neural Architecture Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 2
- Resolution
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- local_arxiv, observed 2026-05-13T23:58:28.699201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation d8499d88-87f7-4b06-917f-47b59241991f · inbound
Complex-Valued GNNs for Distributed Basis-Invariant Control of Planar Systems cites this paper.
Complex-Valued GNNs for Distributed Basis-Invariant Control of Planar Systems Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T20:58:15.930796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 019c4908-2d05-4dc5-ac26-14009ae6193e · inbound
Bridging the Dimensionality Gap: A Taxonomy and Survey of 2D Vision Model Adaptation for 3D Analysis cites this paper.
Bridging the Dimensionality Gap: A Taxonomy and Survey of 2D Vision Model Adaptation for 3D Analysis Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 1
- Resolution
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- local_arxiv, observed 2026-05-13T20:28:13.975396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b5cc5ea8-796c-4042-b9b9-52ac67ccbd40 · inbound
The Topology of Multimodal Fusion: Why Current Architectures Fail at Creative Cognition cites this paper.
The Topology of Multimodal Fusion: Why Current Architectures Fail at Creative Cognition Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 033298db-cbe0-472a-af10-c64aa0574a28 · inbound
LAG-XAI: A Lie-Inspired Affine Geometric Framework for Interpretable Paraphrasing in Transformer Latent Spaces cites this paper.
LAG-XAI: A Lie-Inspired Affine Geometric Framework for Interpretable Paraphrasing in Transformer Latent Spaces Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 7
- Resolution
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- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e422c474-1e6c-434e-8dae-8530b5cefed4 · inbound
Toward a universal foundation model for graph-structured data cites this paper.
Toward a universal foundation model for graph-structured data Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 13
- Resolution
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- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 53e190d6-dafa-464d-8446-bc8e9558e5d7 · inbound
Stability Enhanced Gaussian Process Variational Autoencoders cites this paper.
Stability Enhanced Gaussian Process Variational Autoencoders Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 5e5bb90b-ea81-431a-bac6-e6284347e11b · inbound
Gradient-Based Program Synthesis with Neurally Interpreted Languages cites this paper.
Gradient-Based Program Synthesis with Neurally Interpreted Languages Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 45
- Resolution
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- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6633dec8-1701-4594-a98c-b0103694b8d5 · inbound
Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds cites this paper.
Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 58
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 02cc3c26-f6ca-462f-8cd3-e4eb342bf415 · inbound
Data-driven discovery of polynomial ODEs with provably bounded solutions cites this paper.
Data-driven discovery of polynomial ODEs with provably bounded solutions Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2aecffc3-a247-462c-8479-71ff41d734fc · inbound
Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems cites this paper.
Scale-Aware Adversarial Analysis: A Diagnostic for Generative AI in Multiscale Complex Systems Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 59
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b26066d8-fc85-4b14-b886-c0bdb928adb8 · inbound
Coupled Arnol'd cat maps on circulant graphs cites this paper.
Coupled Arnol'd cat maps on circulant graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cc8f2a7b-f195-4c7b-9c22-56791d393520 · inbound
Coupled Arnol'd cat maps on circulant graphs cites this paper.
Coupled Arnol'd cat maps on circulant graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-22T10:11:22.983654Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 670d610d-5fee-4e1c-8c0e-6a10181385b1 · inbound
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise cites this paper.
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 27
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 19a29799-4642-4ecf-b4a7-396569c13946 · inbound
Cardiac Mesh Flow: One-Step Generation of 3D+t Cardiac Four-Chamber Meshes via Flow Matching cites this paper.
Cardiac Mesh Flow: One-Step Generation of 3D+t Cardiac Four-Chamber Meshes via Flow Matching Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 54
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation be076de8-c906-476a-a293-471c305fb786 · inbound
Geometric Quantum Physics Informed Neural Network cites this paper.
Geometric Quantum Physics Informed Neural Network Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 380552a2-a215-4a47-a2ba-2a148b2c6393 · inbound
Symmetry-Protected Lyapunov Neutral Modes in Equivariant Recurrent Networks cites this paper.
Symmetry-Protected Lyapunov Neutral Modes in Equivariant Recurrent Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 22
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4a4cac36-ff03-4d26-8fda-011eabfee1c8 · inbound
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs cites this paper.
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2e7d4d67-122f-4e41-872f-0b447b2ed916 · inbound
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs cites this paper.
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 225cc586-3575-4edd-b2ce-822e06d1edef · inbound
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs cites this paper.
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:14:03.258395Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 6d238918-dd40-4e86-925b-0636856804c7 · inbound
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs cites this paper.
Reentrant value fields as delayed coupled reaction-diffusion systems on finite graphs Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T00:05:10.032482Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f0373e4f-30f4-4bcf-b608-7f27182e4971 · inbound
Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA cites this paper.
Temporal Reasoning Is Not the Bottleneck: A Probabilistic Inconsistency Framework for Neuro-Symbolic QA Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 3c47b066-d73f-48cf-a6a1-c8cc5ece14b1 · inbound
The Role of Node Features in Graph Pooling cites this paper.
The Role of Node Features in Graph Pooling Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation eee81bd0-11f7-46da-a3b4-e825b9166ec4 · inbound
LINC: Decoupling Local Consequence Scoring from Hidden Matching in Constructive Neural Routing cites this paper.
LINC: Decoupling Local Consequence Scoring from Hidden Matching in Constructive Neural Routing Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 72fc05e1-ab5b-48bd-9f9a-8fdf99a29a4a · inbound
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves cites this paper.
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 8496b239-ac8f-45df-987d-358524bbd7c2 · inbound
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves cites this paper.
Consistent Geometric Deep Learning via Hilbert Bundles and Cellular Sheaves Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T08:59:55.457491Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation f41325d4-2694-4b5d-9957-dd2ef15dd7f2 · inbound
Operator-Guided Invariance Learning for Continuous Reinforcement Learning cites this paper.
Operator-Guided Invariance Learning for Continuous Reinforcement Learning Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 2e3e89ef-14c3-4ab1-8463-f2e0a2475251 · inbound
Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity cites this paper.
Every Feedforward Neural Network Definable in an o-Minimal Structure Has Finite Sample Complexity Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T02:39:30.071842Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.