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Paper Citation Record · LEDGER

PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2306.08827.

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

pith.paper-citation-record.v1
2306.08827 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:16:55.219509Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:36:40.346783Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bf51f58b-7ba0-4b59-8c50-0bd62445300f · inbound

Bayesian Reasoning for Physics Informed Neural Networks cites this paper.

Bayesian Reasoning for Physics Informed Neural Networks PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-24T08:06:03.912121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-24T08:04:59.688875Z digest=sha256:574a3147e7f893dc94ac58008f5a9ff6d2be04823d4a87bf37ff98db8dd547ca

Observation 578997db-9a6a-4dd0-92d4-fcb84cd47d8c · inbound

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning cites this paper.

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 38

Resolution
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no resolver link, observed 2026-08-12T05:16:55.219509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T05:16:55.219509Z digest=sha256:4606f05b9ae60a65ccb1673e2c9de5e4a23bb84ccc9a468c351296a6351c283e

Observation ab36142b-d56f-4140-83cd-cc222e6f07c9 · inbound

jinns: a JAX Library for Physics-Informed Neural Networks cites this paper.

jinns: a JAX Library for Physics-Informed Neural Networks PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-11T12:29:34.537720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:29:34.537720Z digest=sha256:e181366bfc6d310df6b2292c29648d52aa2e5d13bd1190a6887f42886f2b3376

Observation 6f0e5c0b-3bab-4427-8cbc-8767284fd2b9 · inbound

Physics-Informed Neural Networks for Solving the Two-Dimensional Shallow Water Equations with Terrain Topography and Rainfall Source Terms cites this paper.

Physics-Informed Neural Networks for Solving the Two-Dimensional Shallow Water Equations with Terrain Topography and Rainfall Source Terms PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-10T18:25:49.237013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:25:49.237013Z digest=sha256:bdd2fce10876c653ec6e587937f30fefddab47774bae35cd5e38211271edf549

Observation acbc53da-3adc-4a0f-80eb-4ec11bd0adce · inbound

PINNsAgent: Automated PDE Surrogation with Large Language Models cites this paper.

PINNsAgent: Automated PDE Surrogation with Large Language Models PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T17:38:24.167005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:38:24.167005Z digest=sha256:80f602692052b4967f18e8332434f881179dedf6cdb4aca557ae1cfc794ab981

Observation 62378c6c-e8ce-4dca-98a2-f23378caf7f1 · inbound

PDE-DKL: PDE-constrained deep kernel learning in high dimensionality cites this paper.

PDE-DKL: PDE-constrained deep kernel learning in high dimensionality PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-10T00:14:36.531997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T00:14:36.531997Z digest=sha256:fe3754ca352bd41f112988a1613f729e14f2adbe14052fb6fc6d83402be8049a

Observation bcd101a7-9f0d-4c9a-87b1-e1c47c908cb3 · inbound

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning cites this paper.

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T04:19:39.908863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:19:39.908863Z digest=sha256:8348cf0eafafb02faa50026dbcf52dc28bdd9d680b14815a70ce1bac5a7e5df2

Observation c3f0ced4-e1a7-42a6-9117-7f268d899003 · inbound

VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models cites this paper.

VideoPDE: Unified Generative PDE Solving via Video Inpainting Diffusion Models PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T00:31:11.840000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:31:11.840000Z digest=sha256:7b742da39daaaf240571f1cfe07696335f61a463d82be2e12e9eddb60a823031

Observation 0b9cbb66-028d-4b49-9d01-759849e377e1 · inbound

BWLer: Barycentric Weight Layer Elucidates a Precision-Conditioning Tradeoff for PINNs cites this paper.

BWLer: Barycentric Weight Layer Elucidates a Precision-Conditioning Tradeoff for PINNs PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T22:01:49.411540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:01:49.411540Z digest=sha256:74e04cbe1ff978333012f313e4270de32e1bca8db50d42bc85273a60ccb76100

Observation 663e9a92-cc7a-4f86-8c13-777371e81736 · inbound

The Neural Compiler: Program-to-Network Translation for Hybrid Scientific Machine Learning cites this paper.

The Neural Compiler: Program-to-Network Translation for Hybrid Scientific Machine Learning PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-22T08:04:42.971733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-22T08:04:05.604473Z digest=sha256:b691f85aca4434b1f5bd7d7f4d3784facf3540f20616f97956bf0988f5a88de7

Observation 27ed3bcc-2b4e-4ff0-a7e6-39e9e909b766 · inbound

Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence cites this paper.

Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:56:15.373184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-28T16:07:32.118235Z digest=sha256:d8737f21fb7b3adef3b6b9291a7a7d69b8ad6de32e9ff37d50ceb406aefd89cd

Observation 363ee441-0fe2-4772-84cf-112e0df6475a · inbound

TransportBench: A Comprehensive Benchmark for Non-Equilibrium Flow Transport cites this paper.

TransportBench: A Comprehensive Benchmark for Non-Equilibrium Flow Transport PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-07-02T05:36:40.348544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-28T08:07:27.577279Z digest=sha256:a968b250b5503dbe29e074a2af92907ee77a59b600122b66e7565a256349767b

Observation 8da8ae44-98c6-44e7-8a69-7a232a1f9879 · inbound

Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations cites this paper.

Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-06T16:56:19.420787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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