Paper Citation Record · LEDGER

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning

As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2506.19482.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.19482 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:11:55.907765Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 354bf1a5-03c5-4da0-b01f-ade6bd86e61c · outbound

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

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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Observation 29111ed2-9067-4685-8031-e1f12098d780 · outbound

This paper cites A survey of geometric graph neural networks: data structures, models and applications,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning A survey of geometric graph neural networks: data structures, models and applications,

Reference 2

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Observation 82171e25-d9e1-4c2d-98e6-3d06474291c6 · outbound

This paper cites A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems

Reference 3

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Observation 1b6147aa-d5d1-481b-90ce-f0b814922b76 · outbound

This paper cites Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems

Reference 4

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Observation 246c6168-a6c2-4278-bd26-ee6d736e5b5f · outbound

This paper cites Equivariant spatio-temporal attentive graph networks to simulate physical dynamics,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Equivariant spatio-temporal attentive graph networks to simulate physical dynamics,

Reference 5

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Observation fff5cbf7-8368-446a-8313-61429b9e39da · outbound

This paper cites Equivariant graph neural operator for modeling 3d dynamics,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Equivariant graph neural operator for modeling 3d dynamics,

Reference 6

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Observation 6d771464-8685-48cc-84c8-7c33b2cf7364 · outbound

This paper cites De novo design of protein structure and function with rfdiffusion,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning De novo design of protein structure and function with rfdiffusion,

Reference 7

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Observation b4143cde-3a66-4626-b1c8-f0c0bfad2644 · outbound

This paper cites Illuminating protein space with a programmable generative model,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Illuminating protein space with a programmable generative model,

Reference 8

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Observation bfff3790-fa88-4bcb-96c3-de20dfaff704 · outbound

This paper cites E (n) equiv- ariant graph neural networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning E (n) equiv- ariant graph neural networks,

Reference 9

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Observation 8a83b316-b19f-43a9-9f42-64984cbcc039 · outbound

This paper cites The fast multipole method: numerical implementa- tion,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning The fast multipole method: numerical implementa- tion,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.995904Z

Source-reported events for the cited work

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Observation 24664167-f5f2-41e5-9cfb-aaa6925c4edb · outbound

This paper cites Improving equivariant graph neural networks on large geometric graphs via virtual nodes learning,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Improving equivariant graph neural networks on large geometric graphs via virtual nodes learning,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.962809Z

Source-reported events for the cited work

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Observation 6f2a5bb5-0dc8-4f65-bc4b-c72234de04da · outbound

This paper cites Integrating structured biological data by kernel maximum mean discrepancy,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Integrating structured biological data by kernel maximum mean discrepancy,

Reference 12

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Source-reported events for the cited work

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Observation fd96545f-03c7-40ac-90f0-d1f6c2df0472 · outbound

This paper cites Schnet–a deep learning architecture for molecules and materials,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Schnet–a deep learning architecture for molecules and materials,

Reference 13

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Source-reported events for the cited work

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Observation 6b8c390e-0939-4451-948b-2b1fd943aca7 · outbound

This paper cites Directional message passing for molecular graphs,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Directional message passing for molecular graphs,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.488987Z

Source-reported events for the cited work

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Observation 061e9cf1-80a8-42db-b4bc-cb61a5f774f1 · outbound

This paper cites Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

Reference 15

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Observation df51d24b-56f0-4d68-87d7-af94f0a5ac8a · outbound

This paper cites Geometric and physical quantities improve e(3) equivariant message passing,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Geometric and physical quantities improve e(3) equivariant message passing,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.435440Z

Source-reported events for the cited work

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Observation 5cba3f8d-5886-4189-b3ed-9a8db9dd6610 · outbound

This paper cites Se(3)- transformers: 3d roto-translation equivariant attention networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Se(3)- transformers: 3d roto-translation equivariant attention networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.413001Z

Source-reported events for the cited work

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Observation 47db26da-a02c-448a-af51-e22d9f63753b · outbound

This paper cites Equivariant Flows: sampling configurations for multi-body systems with symmetric energies.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Equivariant Flows: sampling configurations for multi-body systems with symmetric energies

Reference 18

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Observation 79b99fb7-50da-4b50-bc59-626ceb25ba94 · outbound

This paper cites Learning from protein structure with geometric vector perceptrons,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Learning from protein structure with geometric vector perceptrons,

Reference 19

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Observation 2f1f67f6-4d77-47b4-8df8-a0b939ec8d4e · outbound

This paper cites Are high- degree representations really unnecessary in equivariant graph neural networks?.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Are high- degree representations really unnecessary in equivariant graph neural networks?

Reference 20

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Observation e9027f56-3f82-43a9-9a16-e4690bdca4d9 · outbound

This paper cites Neural message passing for quantum chemistry,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Neural message passing for quantum chemistry,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.348595Z

Source-reported events for the cited work

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Observation 8a86d18a-8ade-4339-9790-cbba542d3a4f · outbound

This paper cites Graph Classification via Deep Learning with Virtual Nodes.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Graph Classification via Deep Learning with Virtual Nodes

Reference 22

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Observation 97f08c77-9659-46ce-a12a-397e4fd0d9cb · outbound

This paper cites An analysis of virtual nodes in graph neural networks for link prediction,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning An analysis of virtual nodes in graph neural networks for link prediction,

Reference 23

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Observation 655cdac9-45ce-4c3d-8862-71eaa4134757 · outbound

This paper cites Learning physical dynamics with subequivariant graph neural networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Learning physical dynamics with subequivariant graph neural networks,

Reference 24

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Observation ee89221e-ddef-4d4c-9ca1-3e5356d0d666 · outbound

This paper cites Conditional antibody design as 3d equivariant graph translation,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Conditional antibody design as 3d equivariant graph translation,

Reference 25

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Observation 9054ea29-bf5c-42f5-b374-4cb5ee050550 · outbound

This paper cites Graph neural networks: Scalability,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Graph neural networks: Scalability,

Reference 26

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Observation da25675d-349f-44c9-bd27-783eee847916 · outbound

This paper cites Scalable and effective graph neural networks via trainable random walk sampling,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Scalable and effective graph neural networks via trainable random walk sampling,

Reference 27

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Observation febebfec-4143-4f0b-aecd-36917dcb4d20 · outbound

This paper cites Distgnn: Scalable distributed training for large-scale graph neural networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Distgnn: Scalable distributed training for large-scale graph neural networks,

Reference 28

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Observation 3913fcdb-11f5-44c1-bd67-cd6909807a19 · outbound

This paper cites Equivariant graph mechanics networks with constraints,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Equivariant graph mechanics networks with constraints,

Reference 29

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Source-reported events for the cited work

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Observation 6e7d6d15-9142-4581-b7c7-194218549549 · outbound

This paper cites Scalars are universal: Equivariant machine learning, structured like classical physics,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Scalars are universal: Equivariant machine learning, structured like classical physics,

Reference 30

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Observation c209b2de-6ae0-472d-a1bd-0d9f6b993bc6 · outbound

This paper cites Metis—a software package for parti- tioning unstructured graphs, partitioning meshes and computing fill-reducing ordering of sparse matrices,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Metis—a software package for parti- tioning unstructured graphs, partitioning meshes and computing fill-reducing ordering of sparse matrices,

Reference 31

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Observation 0b6d6f15-0a1b-455f-80c2-b212c3a92721 · outbound

This paper cites Neu- ral relational inference for interacting systems,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Neu- ral relational inference for interacting systems,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.144944Z

Source-reported events for the cited work

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Observation b18e4e26-3dd7-478d-b928-f79ab3775f8d · outbound

This paper cites Equivariant graph hierarchy-based neural networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Equivariant graph hierarchy-based neural networks,

Reference 33

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Source-reported events for the cited work

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Observation 805d1739-2512-427e-9664-b49b9c13389a · outbound

This paper cites MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations,

Reference 34

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Observation 955d4570-1206-40b1-93a8-97dc3def7630 · outbound

This paper cites Molecular dynamics trajectory for benchmarking mdanalysis,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Molecular dynamics trajectory for benchmarking mdanalysis,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.101703Z

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Observation c78c45f5-a7e7-46d2-9406-1ee7d9e744b6 · outbound

This paper cites Learning to simulate complex physics with graph networks,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning Learning to simulate complex physics with graph networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.086587Z

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Observation 2c3ce3c2-03a5-4be4-bec4-425007a974ea · outbound

This paper cites La- grangian fluid simulation with continuous convolutions,.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning La- grangian fluid simulation with continuous convolutions,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.072702Z

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Observation 55db67dd-b3ff-4868-96d9-bb85cd67e4ff · outbound

This paper cites SPlisHSPlasH Library.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning SPlisHSPlasH Library

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.057896Z

Source-reported events for the cited work

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Observation 5842ed2f-b19f-4041-bdee-71faae872cd7 · outbound

This paper cites AMONG THEM , F LUID 113K IS OUR GENERATED LARGE -SCALE FLUID SIMULATION DATASET , WHERE EACH GRAPH CONTAINS OVER 100K NODES AND AN AVERAGE OF 1.7M EDGES.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning AMONG THEM , F LUID 113K IS OUR GENERATED LARGE -SCALE FLUID SIMULATION DATASET , WHERE EACH GRAPH CONTAINS OVER 100K NODES AND AN AVERAGE OF 1.7M EDGES

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.044635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9f8e0f90-53f1-402f-8d04-a99948ba6cc3 · outbound

This paper cites (10) 1.5 1 .0 1 .5 3 .0 Balancing factor λ in Eq.

Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning (10) 1.5 1 .0 1 .5 3 .0 Balancing factor λ in Eq

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:11:56.029808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

No inbound Pith citation observations are available.