On the Expressive Power of Permutation-Equivariant Weight-Space Networks | Paper Citation Record

Observation 678d720d-f723-45f1-83de-30ca2076a609 · outbound

This paper cites A convergence theory for deep learning via over-parameterization.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks A convergence theory for deep learning via over-parameterization

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.477480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00e857e9-4640-49b3-be78-d5edcd28c4d5 · outbound

This paper cites Expressive Power of Invariant and Equivariant Graph Neural Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Expressive Power of Invariant and Equivariant Graph Neural Networks

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.506715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7a9a177-61d3-405a-a046-bd365d650536 · outbound

This paper cites A flexible, equivariant framework for subgraph gnns via graph products and graph coarsening.Advances in Neural Information Processing Systems, 37:101168– 101222, 2024.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks A flexible, equivariant framework for subgraph gnns via graph products and graph coarsening.Advances in Neural Information Processing Systems, 37:101168– 101222, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.564047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82b719f3-10e1-4561-95d7-933b55368a48 · outbound

This paper cites Reconciling modern machine-learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Reconciling modern machine-learning practice and the classical bias–variance trade-off.Proceedings of the National Academy of Sciences, 116(32):15849–15854, 2019

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.643595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eae162de-5bb1-4ec3-894f-1f9ed1df51bd · outbound

This paper cites Equivariant Subgraph Aggregation Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Equivariant Subgraph Aggregation Networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.700023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1670c001-9912-4f9c-aedc-1486428775c6 · outbound

This paper cites Weisfeiler and lehman go cellular: Cw networks.Advances in neural information processing systems, 34:2625–2640, 2021.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Weisfeiler and lehman go cellular: Cw networks.Advances in neural information processing systems, 34:2625–2640, 2021

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.774860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94960301-cdce-47f5-b443-4138ed3559f7 · outbound

This paper cites Improving graph neural network expressivity via subgraph isomorphism counting.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1):657–668, 2022.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Improving graph neural network expressivity via subgraph isomorphism counting.IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1):657–668, 2022

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.836584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d24d779-24df-412d-9952-78a5cbfaea71 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

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 22b4a8fb-9bad-4c06-9be3-9a01cd471c08 · outbound

This paper cites Reconstruction for powerful graph representations.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Reconstruction for powerful graph representations

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:05.981214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f81e1b98-d68a-4eab-acdf-16dbe864e76e · outbound

This paper cites Approximation by superpositions of a sigmoidal function.Mathematics of control, signals and systems, 2(4):303–314, 1989.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Approximation by superpositions of a sigmoidal function.Mathematics of control, signals and systems, 2(4):303–314, 1989

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.132429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c3f6bc3-d0e0-4945-b981-df1c3880399a · outbound

This paper cites Laplace redux-effortless bayesian deep learning.Advances in neural information processing systems, 34:20089– 20103, 2021.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Laplace redux-effortless bayesian deep learning.Advances in neural information processing systems, 34:20089– 20103, 2021

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.238178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 219d8ac7-d1e3-4bda-8274-30157626d2f1 · outbound

This paper cites Deep Learning on Implicit Neural Representations of Shapes.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Deep Learning on Implicit Neural Representations of Shapes

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.411369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fab0b478-e5cc-4f99-b71a-c556aa5af340 · outbound

This paper cites Gradient descent finds global minima of deep neural networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Gradient descent finds global minima of deep neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.478623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12f30a35-ff06-4509-abf8-eac3f5dabd0e · outbound

This paper cites From data to functa: Your data point is a function and you can treat it like one.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks From data to functa: Your data point is a function and you can treat it like one

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.540176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62ca243a-a241-4124-8e17-ed7bb0a8d0c1 · outbound

This paper cites Benchmarking graph neural networks.Journal of Machine Learning Research, 24(43):1–48, 2023.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Benchmarking graph neural networks.Journal of Machine Learning Research, 24(43):1–48, 2023

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.597591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f5fa66e-ace5-4fa0-94ad-da233ec32d6f · outbound

This paper cites On the Universality of Rotation Equivariant Point Cloud Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On the Universality of Rotation Equivariant Point Cloud Networks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.663756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 477a6c89-1e1e-4c49-94e9-cd4f70893979 · outbound

This paper cites Classifying the classifier: dissecting the weight space of neural networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Classifying the classifier: dissecting the weight space of neural networks

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.811613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c334e843-8699-4ea7-a3e5-c8e8cfd1ab8b · outbound

This paper cites Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Topological Blindspots: Understanding and Extending Topological Deep Learning Through the Lens of Expressivity

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:06.996061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfa8f03c-7b01-4a1d-a056-4f40f4a24544 · outbound

This paper cites On the expressive power of gnn derivatives.arXiv preprint arXiv:2510.02565, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On the expressive power of gnn derivatives.arXiv preprint arXiv:2510.02565, 2025

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.166122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09f2e84d-3538-469a-99a6-15428c0d191f · outbound

This paper cites Fs-kan: Permutation equivariant kolmogorov-arnold networks via function sharing.arXiv preprint arXiv:2509.24472, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Fs-kan: Permutation equivariant kolmogorov-arnold networks via function sharing.arXiv preprint arXiv:2509.24472, 2025

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.318638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 188e318c-1c99-4ff5-a5e0-bf7e4238166e · outbound

This paper cites Equivariance everywhere all at once: A recipe for graph foundation models.arXiv preprint arXiv:2506.14291, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Equivariance everywhere all at once: A recipe for graph foundation models.arXiv preprint arXiv:2506.14291, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.503589Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15408376-8015-452b-b819-5de0fff32aee · outbound

This paper cites Understanding and extending subgraph gnns by rethinking their symmetries.Advances in Neural Information Processing Systems, 35:31376– 31390, 2022.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Understanding and extending subgraph gnns by rethinking their symmetries.Advances in Neural Information Processing Systems, 35:31376– 31390, 2022

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.554748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2789b23-458f-490e-a21c-7dfe8c037694 · outbound

This paper cites Gradmetanet: An equivariant architecture for learning on gradients.arXiv preprint arXiv:2507.01649, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Gradmetanet: An equivariant architecture for learning on gradients.arXiv preprint arXiv:2507.01649, 2025

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.674877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13463461-05c5-431c-9afa-9ed583057f40 · outbound

This paper cites Descriptive complexity, canonisation, and definable graph structure theory, volume 47 of lecture notes in logic.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Descriptive complexity, canonisation, and definable graph structure theory, volume 47 of lecture notes in logic

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:07.822854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21ba0767-7e07-4103-a9d1-11f1e134ecaa · outbound

This paper cites Studying Large Language Model Generalization with Influence Functions.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Studying Large Language Model Generalization with Influence Functions

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.014934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e1ec789-7bf2-4269-aa35-249f51c2a685 · outbound

This paper cites Learning both weights and connections for efficient neural network.Advances in neural information processing systems, 28, 2015.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Learning both weights and connections for efficient neural network.Advances in neural information processing systems, 28, 2015

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.166896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91de4e61-9a4d-4f18-bc16-302de02d76c5 · outbound

This paper cites Optimal brain surgeon and general network pruning.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Optimal brain surgeon and general network pruning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.265028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d529b0e9-09d8-41c0-a55e-8374e05cd6f4 · outbound

This paper cites Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Sparsified Model Zoo Twins: Investigating Populations of Sparsified Neural Network Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.471267Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a3de752-64aa-4a5d-a3e4-17f7bf91d1f0 · outbound

This paper cites Eurosat model zoo: A dataset and benchmark on populations of neural networks and its sparsified model twins.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Eurosat model zoo: A dataset and benchmark on populations of neural networks and its sparsified model twins

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.557974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f912fad-50b0-4c1f-843d-ac8c0d5c6d1b · outbound

This paper cites Weisfeiler Leman for Euclidean Equivariant Machine Learning.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Weisfeiler Leman for Euclidean Equivariant Machine Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.669917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea237bc7-cf93-4537-b934-76845b9cb3d2 · outbound

This paper cites Complete neural networks for complete euclidean graphs.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Complete neural networks for complete euclidean graphs

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.775794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0b71c8d-0291-4c8b-aff6-9520140ebe94 · outbound

This paper cites Approximation capabilities of multilayer feedforward networks.Neural networks, 4(2):251–257, 1991.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Approximation capabilities of multilayer feedforward networks.Neural networks, 4(2):251–257, 1991

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:08.977879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39313fdf-341f-4124-b2ed-fe35d6a89729 · outbound

This paper cites Scalable marginal likelihood estimation for model selection in deep learning.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Scalable marginal likelihood estimation for model selection in deep learning

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.068736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9fedd2e-8d86-4b24-9413-008eff1bbddb · outbound

This paper cites Scale equivariant graph metanetworks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Scale equivariant graph metanetworks

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.149938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f1d28ca6-4323-443d-b61e-b12f5061a2f8 · outbound

This paper cites Scaling Laws for Neural Language Models.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Scaling Laws for Neural Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.239460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab167e78-1c4c-4591-819f-942cba2990eb · outbound

This paper cites Universal invariant and equivariant graph neural networks.Advances in neural information processing systems, 32, 2019.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Universal invariant and equivariant graph neural networks.Advances in neural information processing systems, 32, 2019

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.343916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68155baa-2bb3-400b-963a-188f47a938bb · outbound

This paper cites Graph Neural Networks for Learning Equivariant Representations of Neural Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Graph Neural Networks for Learning Equivariant Representations of Neural Networks

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.482523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9b0187d-8397-481b-b3f1-0bee311f9a2b · outbound

This paper cites Understanding black-box predictions via influence functions.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Understanding black-box predictions via influence functions

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.550168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99953767-73ec-4f4b-9ef4-05067a020d09 · outbound

This paper cites Optimal brain damage.Advances in neural information processing systems, 2, 1989.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Optimal brain damage.Advances in neural information processing systems, 2, 1989

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.582367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0c3f535-3bd2-4caf-9316-70711cda3293 · outbound

This paper cites Sign and Basis Invariant Networks for Spectral Graph Representation Learning.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Sign and Basis Invariant Networks for Spectral Graph Representation Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.614855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fee813ec-4f6b-47ee-ac65-a3dea7adc9c9 · outbound

This paper cites Graph Metanetworks for Processing Diverse Neural Architectures.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Graph Metanetworks for Processing Diverse Neural Architectures

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.698800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 147bd497-6621-452b-8b5a-ec05232852a1 · outbound

This paper cites Provably powerful graph networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Provably powerful graph networks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.873966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e2175f1-e952-454b-8dd1-3d2477d87a97 · outbound

This paper cites On the universality of invariant networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On the universality of invariant networks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:09.976917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 585bca5f-8982-4f1e-aa26-56e31bbb9e5d · outbound

This paper cites On learning sets of symmetric elements.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On learning sets of symmetric elements

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.085018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4685644b-6a97-439f-81d5-4ea33ef2e097 · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106, 2021.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Nerf: Representing scenes as neural radiance fields for view synthesis.Communications of the ACM, 65(1):99–106, 2021

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.181396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e63864bd-d3e2-426d-96f7-7d93cbbaffa5 · outbound

This paper cites On the number of linear regions of deep neural networks.Advances in neural information processing systems, 27, 2014.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On the number of linear regions of deep neural networks.Advances in neural information processing systems, 27, 2014

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.288123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e242d84c-762a-435d-85af-f7c68223a3da · outbound

This paper cites Weisfeiler and leman go neural: Higher-order graph neural networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Weisfeiler and leman go neural: Higher-order graph neural networks

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.387797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a80cbd91-7f27-419e-b07e-0d909a149779 · outbound

This paper cites Weisfeiler and leman go machine learning: The story so far.Journal of Machine Learning Research, 24(333):1–59, 2023.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Weisfeiler and leman go machine learning: The story so far.Journal of Machine Learning Research, 24(333):1–59, 2023

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.498253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d9d6f6e0-c7a7-4f4e-80cc-fa0933fc542e · outbound

This paper cites Equivariant architectures for learning in deep weight spaces.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Equivariant architectures for learning in deep weight spaces

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.604188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a32fc744-d197-4760-b1b5-e822a4f55039 · outbound

This paper cites On Universality of Deep Equivariant Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On Universality of Deep Equivariant Networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.702786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40fb3615-c3e3-457e-b2df-17193d1d7487 · outbound

This paper cites On universality classes of equivariant networks.arXiv preprint arXiv:2506.02293, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On universality classes of equivariant networks.arXiv preprint arXiv:2506.02293, 2025

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.812522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 991ba3b6-89fd-4fc9-815c-b2357090d74f · outbound

This paper cites Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Learning on LoRAs: GL-Equivariant Processing of Low-Rank Weight Spaces for Large Finetuned Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:10.916857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad0a1aa5-d383-46fc-ac5d-e80066ecb7f8 · outbound

This paper cites Pointnet: Deep learning on point sets for 3d classification and segmentation.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Pointnet: Deep learning on point sets for 3d classification and segmentation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.031825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a68b52f3-7821-4527-98a4-7bdaecab68e6 · outbound

This paper cites On the expressive power of deep neural networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On the expressive power of deep neural networks

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.115911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc315ab4-ba47-435f-a06d-9840b4134b45 · outbound

This paper cites Universal equivariant multilayer perceptrons.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Universal equivariant multilayer perceptrons

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.187625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76b450be-868c-478f-b36f-fd0938cd12a7 · outbound

This paper cites A persistent weisfeiler-lehman procedure for graph classification.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks A persistent weisfeiler-lehman procedure for graph classification

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.255530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbd69588-d86f-47b2-acc1-303a62a533d7 · outbound

This paper cites Self-supervised representation learning on neural network weights for model characteristic prediction.Advances in Neural Information Processing Systems, 34: 16481–16493, 2021.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Self-supervised representation learning on neural network weights for model characteristic prediction.Advances in Neural Information Processing Systems, 34: 16481–16493, 2021

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.329514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c572c656-dc5b-4074-8a0b-a48d210e6b53 · outbound

This paper cites A model zoo on phase transitions in neural networks.arXiv preprint arXiv:2504.18072, 2025.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks A model zoo on phase transitions in neural networks.arXiv preprint arXiv:2504.18072, 2025

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.397303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cabfa7a2-c62d-4c42-83e5-d2a3c16decc1 · outbound

This paper cites On Universal Equivariant Set Networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks On Universal Equivariant Set Networks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.466613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99ac3bc1-01a6-46f1-845f-0a617a97339c · outbound

This paper cites Bounding and counting linear regions of deep neural networks.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Bounding and counting linear regions of deep neural networks

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.538644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d85b19ee-7c3f-41db-9d99-aa97e60b1f60 · outbound

This paper cites Improved Generalization of Weight Space Networks via Augmentations.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Improved Generalization of Weight Space Networks via Augmentations

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.582783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ffb03c2-bcf2-4ce6-b0d6-10f1c1f43548 · outbound

This paper cites Implicit neural representations with periodic activation functions.Advances in neural information processing systems, 33: 7462–7473, 2020.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Implicit neural representations with periodic activation functions.Advances in neural information processing systems, 33: 7462–7473, 2020

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.656557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95031fd6-9f2f-4260-a266-d8994637dc6d · outbound

This paper cites Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Balancing Efficiency and Expressiveness: Subgraph GNNs with Walk-Based Centrality

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.727855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7cc81c8a-5044-4c51-8e2c-e44ee75d9e5d · outbound

This paper cites Monomial matrix group equivariant neural functional networks.Advances in Neural Information Processing Systems, 37:48628–48665, 2024.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Monomial matrix group equivariant neural functional networks.Advances in Neural Information Processing Systems, 37:48628–48665, 2024

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.800730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8294f25-c8e6-494e-a9ab-9cc49fdf9137 · outbound

This paper cites Predicting Neural Network Accuracy from Weights.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Predicting Neural Network Accuracy from Weights

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.878262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73451373-a53c-4a6b-bbe4-b578210199e1 · outbound

This paper cites Equivariant polynomial functional networks.arXiv preprint arXiv:2410.04213, 2024.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Equivariant polynomial functional networks.arXiv preprint arXiv:2410.04213, 2024

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:11.945082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b57b6c1-6433-4c0f-852e-623631f5dcd4 · outbound

This paper cites Recurrent Diffusion for Large-Scale Parameter Generation.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Recurrent Diffusion for Large-Scale Parameter Generation

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.015687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f1dfe32-7132-4943-aaed-c20dd3392a02 · outbound

This paper cites How Powerful are Graph Neural Networks?.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks How Powerful are Graph Neural Networks?

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.089593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a8918936-f096-47df-92e7-5062d3ec87ad · outbound

This paper cites Deep sets.Advances in neural information processing systems, 30, 2017.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Deep sets.Advances in neural information processing systems, 30, 2017

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.158277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63adac97-e8da-44ab-a597-fa63bd1ec2d2 · outbound

This paper cites Nested graph neural networks.Advances in Neural Information Processing Systems, 34:15734–15747, 2021.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Nested graph neural networks.Advances in Neural Information Processing Systems, 34:15734–15747, 2021

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.232590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff5a3589-2b10-4b31-83c7-c67f02d2cfb1 · outbound

This paper cites Permutation equivariant neural functionals.Advances in neural information processing systems, 36: 24966–24992, 2023.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Permutation equivariant neural functionals.Advances in neural information processing systems, 36: 24966–24992, 2023

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.301984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f71b0ac0-646f-4669-98a9-3137ce06d70e · outbound

This paper cites Neural functional transformers.Advances in neural information processing systems, 36:77485–77502, 2023.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Neural functional transformers.Advances in neural information processing systems, 36:77485–77502, 2023

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.407930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9428cbfd-11df-46d3-be87-c00f911d520b · outbound

This paper cites Universal neural functionals.Advances in neural information processing systems, 37:104754–104775, 2024.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Universal neural functionals.Advances in neural information processing systems, 37:104754–104775, 2024

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.483578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 889ca7df-ee78-4cbc-9c2e-46a5cecfe353 · outbound

This paper cites preserved.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks preserved

Reference 74

Resolution: malformed identifier; no resolver link, observed 2026-08-03T05:57:12.558472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6047aedf-473d-4401-9e23-80a82dd5a22d · outbound

This paper cites an unresolved cited work.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Unresolved cited work

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.630491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4307469c-30c3-4f07-b2dc-32643cd8344d · outbound

This paper cites Before proving Theorem F.9, we introduce a convenient class of functions that captures the geometric complexity of ReLU networks with a fixed architecture.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Before proving Theorem F.9, we introduce a convenient class of functions that captures the geometric complexity of ReLU networks with a fixed architecture

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.701441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d778a3f3-dea0-4047-b3b5-8dd0c2632167 · outbound

This paper cites ,vj,rj }(233) for somev j,ℓ ∈Xwith1≤r j ≤R.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks ,vj,rj }(233) for somev j,ℓ ∈Xwith1≤r j ≤R

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.773766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df35696d-9925-477c-accd-13f140a5a1a7 · outbound

This paper cites an unresolved cited work.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.848441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 093aceea-16aa-42f1-8200-1efcd3132f07 · outbound

This paper cites f(x) =A j(x)∀x∈P j.(235) We refer toP 1,.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks f(x) =A j(x)∀x∈P j.(235) We refer toP 1,

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.920461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e4185c3-a4dc-44fd-82c1-0f6b82d5f271 · outbound

This paper cites an unresolved cited work.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks Unresolved cited work

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:12.967656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82934abb-fa1b-4cf2-919b-1481cb1f5ff3 · outbound

This paper cites If P has R vertices, it has at most R(R−1)/2 edges.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks If P has R vertices, it has at most R(R−1)/2 edges

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-03T05:57:13.039781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 729b3ff4-0b09-4b46-aebb-0bcf21c07b53 · outbound

This paper cites ,v(k) j,rk j },(242) with1≤r k j ≤Randv (k) j,ℓ ∈X; 3.f k(x) =A (k) j (x)for allx∈P (k) j.

On the Expressive Power of Permutation-Equivariant Weight-Space Networks ,v(k) j,rk j },(242) with1≤r k j ≤Randv (k) j,ℓ ∈X; 3.f k(x) =A (k) j (x)for allx∈P (k) j

Reference 82

Resolution: malformed identifier; no resolver link, observed 2026-08-03T05:57:13.128467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers