Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-09T08:52:43.105057Z
Paper Citation Record · LEDGER
Stability of Flow Models for Graph Signals
As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2607.07510.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
53 of 53 outbound references displayed
- verified exact2
- verified fuzzy48
- unresolved3
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e6b11651-bf3b-4946-b1af-7e13e3465176 · outbound
This paper cites Flow matching for generative modeling,.
Stability of Flow Models for Graph Signals Flow matching for generative modeling,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.611729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4dc28873-6bf4-457e-b28d-7a9b36997d0e · outbound
This paper cites Denoising diffusion probabilistic models,.
Stability of Flow Models for Graph Signals Denoising diffusion probabilistic models,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.630802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 919881b7-1c04-40d8-b14e-30d8952db382 · outbound
This paper cites Neural ordinary differential equations,.
Stability of Flow Models for Graph Signals Neural ordinary differential equations,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.636497Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aff71566-db53-41bf-b78c-79771c89ee21 · outbound
This paper cites Graph normalizing flows,.
Stability of Flow Models for Graph Signals Graph normalizing flows,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.605106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0244a2ae-d46b-4821-8ac1-c2ef3f4ba537 · outbound
This paper cites Permu- tation invariant graph generation via score-based generative modeling,.
Stability of Flow Models for Graph Signals Permu- tation invariant graph generation via score-based generative modeling,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.610006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 03634508-a55e-4bfd-8b45-66a3787873bb · outbound
This paper cites Score-based generative modeling of graphs via the system of stochastic differential equations,.
Stability of Flow Models for Graph Signals Score-based generative modeling of graphs via the system of stochastic differential equations,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.646855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0b9082e2-6890-464d-9f0c-325f411f6a54 · outbound
This paper cites Generative diffusion models on graphs: Methods and applications,.
Stability of Flow Models for Graph Signals Generative diffusion models on graphs: Methods and applications,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.596079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ad5018a1-2c8d-43f1-9cc6-66fb71426408 · outbound
This paper cites Digress: Discrete denoising diffusion for graph generation,.
Stability of Flow Models for Graph Signals Digress: Discrete denoising diffusion for graph generation,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.591185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5d238831-2451-4c84-9ca0-1b63a2f858d3 · outbound
This paper cites Prior-informed flow matching for graph reconstruction,.
Stability of Flow Models for Graph Signals Prior-informed flow matching for graph reconstruction,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.662822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d84d195e-1658-449d-bedf-4de6c0cddf27 · outbound
This paper cites Graph-aware diffusion for signal generation,.
Stability of Flow Models for Graph Signals Graph-aware diffusion for signal generation,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.657013Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation aa3ea01e-d888-4c2d-bae4-95b93a3d640a · outbound
This paper cites Graph signal generative diffusion models,.
Stability of Flow Models for Graph Signals Graph signal generative diffusion models,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.638469Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f7017ed7-f338-4620-bfae-90d729db91c1 · outbound
This paper cites Graph signal diffusion model for collaborative filtering,.
Stability of Flow Models for Graph Signals Graph signal diffusion model for collaborative filtering,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.626859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a2c3ac4e-1b0d-4273-9790-03d7d7d8d5a9 · outbound
This paper cites Topological schr ¨odinger bridge matching,.
Stability of Flow Models for Graph Signals Topological schr ¨odinger bridge matching,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.651370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation eefbca80-4252-40eb-a037-521a5d7793be · outbound
This paper cites Graph signal processing: Overview, challenges, and applications,.
Stability of Flow Models for Graph Signals Graph signal processing: Overview, challenges, and applications,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.632727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d5bb331a-3371-4e83-9177-12b714396df8 · outbound
This paper cites A graph signal processing perspective on functional brain imaging,.
Stability of Flow Models for Graph Signals A graph signal processing perspective on functional brain imaging,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.655051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 62191712-29d1-4a4a-8bc0-e0f787ab55ec · outbound
This paper cites Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting,.
Stability of Flow Models for Graph Signals Spatio-temporal graph convolutional networks: A deep learning framework for traffic forecasting,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.588064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 54a61c8c-7a46-4777-948e-71e9b60782de · outbound
This paper cites Graph signal processing in applications to sensor networks, smart grids, and smart cities,.
Stability of Flow Models for Graph Signals Graph signal processing in applications to sensor networks, smart grids, and smart cities,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.649279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 09dfc9dc-afcd-43d5-9830-cb144e3a2455 · outbound
This paper cites Grid-graph signal processing (Grid- GSP): A graph signal processing framework for the power grid,.
Stability of Flow Models for Graph Signals Grid-graph signal processing (Grid- GSP): A graph signal processing framework for the power grid,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.642853Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fc0b109b-460f-42c2-ba54-bf49343d6b76 · outbound
This paper cites Graph Signal Diffusion Models for Wireless Resource Allocation.
Stability of Flow Models for Graph Signals Graph Signal Diffusion Models for Wireless Resource Allocation
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T08:56:06.377462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5f46f40e-0966-4e39-a2f8-9c433ba0c0d4 · outbound
This paper cites Data augmentation in classification and segmentation: A survey and new strategies,.
Stability of Flow Models for Graph Signals Data augmentation in classification and segmentation: A survey and new strategies,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.674567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4a823a87-10fc-4953-8c8c-1420317e70a5 · outbound
This paper cites Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations.
Stability of Flow Models for Graph Signals Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.640900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 46f25580-dff4-4685-86be-3cd797ff6f94 · outbound
This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.
Stability of Flow Models for Graph Signals Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T08:56:06.380407Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 398c2962-a756-4690-ad61-6e31cfc66871 · outbound
This paper cites Intriguing properties of neural networks,.
Stability of Flow Models for Graph Signals Intriguing properties of neural networks,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.603687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0cb5fa01-2312-4406-af68-ef37eba91cba · outbound
This paper cites Stability and generalization.
Stability of Flow Models for Graph Signals Stability and generalization
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.653155Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d03f158a-1aae-485b-a3c8-67b660c55bfd · outbound
This paper cites Adversarial attacks on neural networks for graph data,.
Stability of Flow Models for Graph Signals Adversarial attacks on neural networks for graph data,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.597634Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 66c1faf1-b372-47c3-ae34-487db851dc84 · outbound
This paper cites an unresolved cited work.
Stability of Flow Models for Graph Signals Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T08:56:06.589521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 47b35b6b-6675-4a09-9157-b250fc373e94 · outbound
This paper cites On the use of correlation as a measure of network connectivity,.
Stability of Flow Models for Graph Signals On the use of correlation as a measure of network connectivity,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.592846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9d03f4a3-4ac0-44bb-bfe9-02ba35d2319a · outbound
This paper cites Connecting the dots: Identifying network structure via graph signal processing,.
Stability of Flow Models for Graph Signals Connecting the dots: Identifying network structure via graph signal processing,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.606655Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 62fe9c71-52f6-4e1c-8d1f-79eaf8b71493 · outbound
This paper cites Learning graphs from data: A signal representation perspective.
Stability of Flow Models for Graph Signals Learning graphs from data: A signal representation perspective
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.628879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation cc5390f5-d5bf-4552-8b61-f7bbd4231a6f · outbound
This paper cites Stability properties of graph neural networks,.
Stability of Flow Models for Graph Signals Stability properties of graph neural networks,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.594413Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2bf99ede-c9a4-4ff1-8c33-c75d29cd3dbb · outbound
This paper cites Transferability properties of graph neural networks,.
Stability of Flow Models for Graph Signals Transferability properties of graph neural networks,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.644701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a6b1097f-c86a-4650-a168-edd4d84836e4 · outbound
This paper cites Interpretable stability bounds for spectral graph filters,.
Stability of Flow Models for Graph Signals Interpretable stability bounds for spectral graph filters,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.621799Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2be2100d-a794-45a3-b699-76a4bfb25a34 · outbound
This paper cites Trans- ferability of spectral graph convolutional neural networks,.
Stability of Flow Models for Graph Signals Trans- ferability of spectral graph convolutional neural networks,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.586438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1ba2b856-0b8c-455a-9df3-a7222b15c976 · outbound
This paper cites Equivariant flows: Exact likelihood generative learning for symmetric densities,.
Stability of Flow Models for Graph Signals Equivariant flows: Exact likelihood generative learning for symmetric densities,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.618411Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e1ed388f-f4e4-4856-8b35-e9588abdbaf3 · outbound
This paper cites Graph filters for signal processing and machine learning on graphs,.
Stability of Flow Models for Graph Signals Graph filters for signal processing and machine learning on graphs,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.634642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9c4e7071-0790-4fee-9bbc-f72d35b17e33 · outbound
This paper cites Convolutional neural network architectures for signals supported on graphs,.
Stability of Flow Models for Graph Signals Convolutional neural network architectures for signals supported on graphs,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.660923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 028ae26f-21ad-4cce-aa67-9c8624d1a25c · outbound
This paper cites Semi-supervised classification with graph convolutional networks,.
Stability of Flow Models for Graph Signals Semi-supervised classification with graph convolutional networks,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.658953Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation fb56dd24-d73f-4a28-a3f2-2391db2e4173 · outbound
This paper cites Convolutional neural networks on graphs with fast localized spectral filtering,.
Stability of Flow Models for Graph Signals Convolutional neural networks on graphs with fast localized spectral filtering,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.672659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 4a1467e7-2005-4a0b-84d7-cf29b895993e · outbound
This paper cites Graph neural networks: Architec- tures, stability and transferability,.
Stability of Flow Models for Graph Signals Graph neural networks: Architec- tures, stability and transferability,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.670639Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 177906cd-de83-4ec6-b71b-a317b8d6dca8 · outbound
This paper cites Score-based generative modeling through stochastic differ- ential equations,.
Stability of Flow Models for Graph Signals Score-based generative modeling through stochastic differ- ential equations,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.616624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0ef97fc9-7135-4189-afc9-74bb2e05be24 · outbound
This paper cites Improved denoising diffusion probabilis- tic models,.
Stability of Flow Models for Graph Signals Improved denoising diffusion probabilis- tic models,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.613368Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6689c14d-840e-4d11-a464-c97102bc9d7c · outbound
This paper cites Villaniet al.,Optimal transport: old and new.
Stability of Flow Models for Graph Signals Villaniet al.,Optimal transport: old and new
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.602157Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b6ea9668-43b0-4975-8328-d48c7ac69965 · outbound
This paper cites an unresolved cited work.
Stability of Flow Models for Graph Signals Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T08:56:06.664510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a1410777-acd9-48a2-baa8-172bcfe4ed1a · outbound
This paper cites Robust graph neural networks via probabilistic lipschitz constraints,.
Stability of Flow Models for Graph Signals Robust graph neural networks via probabilistic lipschitz constraints,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.620065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 03d54a4b-af3f-457b-aa43-e00f4385087a · outbound
This paper cites Training stable graph neural networks through constrained learning,.
Stability of Flow Models for Graph Signals Training stable graph neural networks through constrained learning,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.668510Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 888202af-1f4a-46ce-bbf0-a7e36d5e242f · outbound
This paper cites an unresolved cited work.
Stability of Flow Models for Graph Signals Unresolved cited work
Reference 46
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T08:56:06.625125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 21557102-6c62-4a5c-9520-7e4fceb82b9c · outbound
This paper cites Stochastic blockmodels: First steps.
Stability of Flow Models for Graph Signals Stochastic blockmodels: First steps
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.599180Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 46f9197f-b8a1-4b35-aa2f-e035db58d78d · outbound
This paper cites Graph frequency analysis of brain signals,.
Stability of Flow Models for Graph Signals Graph frequency analysis of brain signals,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.676462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b915525d-2bf3-4622-815f-68bdc71dcf5d · outbound
This paper cites Decoupling of brain function from structure reveals regional behavioral specialization in humans,.
Stability of Flow Models for Graph Signals Decoupling of brain function from structure reveals regional behavioral specialization in humans,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.666507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1818fe5a-66ee-46e5-b821-fdaeb46ad8f5 · outbound
This paper cites Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,.
Stability of Flow Models for Graph Signals Sigmoid-weighted linear units for neural network function approximation in reinforcement learning,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.614996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 76274b02-b98e-40a3-a2e9-4f1d61cbf06e · outbound
This paper cites A kernel two-sample test.
Stability of Flow Models for Graph Signals A kernel two-sample test
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.623380Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation dec15c13-a4b5-4e4b-8240-1678b11a4eaa · outbound
This paper cites Lipschitz regularity of deep neural networks: Analysis and efficient estimation,.
Stability of Flow Models for Graph Signals Lipschitz regularity of deep neural networks: Analysis and efficient estimation,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.608388Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 502af415-ea88-4d05-a665-00af205671ec · outbound
This paper cites Learning by transference: Training graph neural networks on growing graphs,.
Stability of Flow Models for Graph Signals Learning by transference: Training graph neural networks on growing graphs,
Reference 53
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- verified fuzzy
- raw_fallback, observed 2026-07-09T08:56:06.600729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
No inbound Pith citation observations are available.