Paper Citation Record · LEDGER

Learning to Simulate Complex Physics with Graph Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2002.09405.

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

pith.paper-citation-record.v1
2002.09405 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:31:29.850085Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

448
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 8dbc658d-2344-4448-8b32-81db88376b17 · inbound

Rigid Body Adversarial Attacks cites this paper.

Rigid Body Adversarial Attacks Learning to Simulate Complex Physics with Graph Networks

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-08T18:31:29.850085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 318a4edd-dd70-4231-a710-c9ab3471051d · inbound

Dynamical Data for More Efficient and Generalizable Learning: A Case Study in Disordered Elastic Networks cites this paper.

Dynamical Data for More Efficient and Generalizable Learning: A Case Study in Disordered Elastic Networks Learning to Simulate Complex Physics with Graph Networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T13:45:30.197000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b240076-3767-4425-b50f-7fdd72910282 · inbound

Drag modelling for flows through assemblies of spherical particles with machine learning: A comparison of approaches cites this paper.

Drag modelling for flows through assemblies of spherical particles with machine learning: A comparison of approaches Learning to Simulate Complex Physics with Graph Networks

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-06T19:20:44.506156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a671fdaf-0abf-4e7a-9392-dab7037b262f · inbound

Graph Neural Network Surrogates for Contacting Deformable Bodies with Necessary and Sufficient Contact Detection cites this paper.

Graph Neural Network Surrogates for Contacting Deformable Bodies with Necessary and Sufficient Contact Detection Learning to Simulate Complex Physics with Graph Networks

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T16:31:00.356393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b70fd527-87bd-4c62-8aa7-a2132ce7acc5 · inbound

PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling cites this paper.

PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling Learning to Simulate Complex Physics with Graph Networks

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T10:01:13.623855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7a97983b-36ba-4f43-b32a-0731443b9aad · inbound

R5DGS: Semantic-Aware 4D Gaussian Splatting with Rigid Body Constraints for Efficient Dynamic Scene Reconstruction cites this paper.

R5DGS: Semantic-Aware 4D Gaussian Splatting with Rigid Body Constraints for Efficient Dynamic Scene Reconstruction Learning to Simulate Complex Physics with Graph Networks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-29T22:44:01.261236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fa86bcfd-2f7b-419a-855d-08d05d6c0d81 · inbound

Attention-based optimizer for symmetry finding cites this paper.

Attention-based optimizer for symmetry finding Learning to Simulate Complex Physics with Graph Networks

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:31.331279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c68c420f-1c54-453e-af6e-c2f2edb5cc1a · inbound

Physically Viable World Models: A Case for Query-Conditioned Embodied AI cites this paper.

Physically Viable World Models: A Case for Query-Conditioned Embodied AI Learning to Simulate Complex Physics with Graph Networks

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-06-29T09:13:16.544337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 08d04187-0289-4195-86d0-1393b4e64dd2 · inbound

Attention mechanism for scalable mesh-based neural surrogates of free-surface fluids cites this paper.

Attention mechanism for scalable mesh-based neural surrogates of free-surface fluids Learning to Simulate Complex Physics with Graph Networks

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-06-26T06:19:03.844593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74429b51-0385-46fd-afb7-21f7376d1204 · inbound

Label-Free Finite-Volume-Residual Training of Attention Graph Neural Networks for Coupled Thermo-Fluid Fields cites this paper.

Label-Free Finite-Volume-Residual Training of Attention Graph Neural Networks for Coupled Thermo-Fluid Fields Learning to Simulate Complex Physics with Graph Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T10:13:39.803771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4103668e-4860-438a-b0a8-0cddca48fbd9 · inbound

Hybrid Lagrangian-Eulerian Model for Lagrangian Fluid Simulation cites this paper.

Hybrid Lagrangian-Eulerian Model for Lagrangian Fluid Simulation Learning to Simulate Complex Physics with Graph Networks

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T00:30:47.327874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3b6fc2e-69e1-42f2-8715-c95bb0e63be2 · inbound

Enactive Artificial Intelligence: A Decision-Centric Architecture for Complex Systems cites this paper.

Enactive Artificial Intelligence: A Decision-Centric Architecture for Complex Systems Learning to Simulate Complex Physics with Graph Networks

Reference 121

Resolution: unresolved; no resolver link, observed 2026-08-05T19:30:33.780115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.