Paper Citation Record · LEDGER

Interpretable Machine Learning in Physics: A Review

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2503.23616.

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

pith.paper-citation-record.v1
2503.23616 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:54:21.179836Z

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
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malformed identifier0
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External citation measurements

0
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 dc7f184b-573b-499a-b6b8-58aa7914e608 · inbound

Quantum computing and artificial intelligence: status and perspectives cites this paper.

Quantum computing and artificial intelligence: status and perspectives Interpretable Machine Learning in Physics: A Review

Reference 209

Resolution: unresolved; no resolver link, observed 2026-08-07T12:54:21.179836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c6e40ba-5d5b-4c6f-ac50-0655c3dc5464 · inbound

Sequence-Model-Guided Measurement Selection for Quantum State Learning cites this paper.

Sequence-Model-Guided Measurement Selection for Quantum State Learning Interpretable Machine Learning in Physics: A Review

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-06T17:52:07.685443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c38186c-e9cc-427a-a301-aa0883eb46b7 · inbound

Artificial intelligence for representing and characterizing quantum systems cites this paper.

Artificial intelligence for representing and characterizing quantum systems Interpretable Machine Learning in Physics: A Review

Reference 277

Resolution: unresolved; no resolver link, observed 2026-08-05T05:50:39.845047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0181203b-9211-4235-a60b-03734cd7a177 · inbound

Learning Minimal Representations of Many-Body Physics from Snapshots of a Quantum Simulator cites this paper.

Learning Minimal Representations of Many-Body Physics from Snapshots of a Quantum Simulator Interpretable Machine Learning in Physics: A Review

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-18T16:16:35.916616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a082e15b-97a1-470d-b90e-7ed1f2db446b · inbound

Active Matter as a framework for living systems-inspired Robophysics cites this paper.

Active Matter as a framework for living systems-inspired Robophysics Interpretable Machine Learning in Physics: A Review

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-03T21:34:53.279643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e05835df-d574-4a8b-b15f-d0ade9117df6 · inbound

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging cites this paper.

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Interpretable Machine Learning in Physics: A Review

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-17T01:08:47.511459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f6dc21c7-1100-4891-8ae5-08ead9ac31f4 · inbound

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging cites this paper.

KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging Interpretable Machine Learning in Physics: A Review

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T18:00:48.032536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e9bfddb-8324-47ca-a108-20ed154e9c65 · inbound

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations cites this paper.

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations Interpretable Machine Learning in Physics: A Review

Reference 83

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:41:17.983735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 541f4e68-705f-424d-992f-39bb7783f78c · inbound

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane cites this paper.

Explainable AI for Jet Tagging: A Comparative Study of GNNExplainer, GNNShap, and GradCAM for Jet Tagging in the Lund Jet Plane Interpretable Machine Learning in Physics: A Review

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:01:14.819769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 56f9a27c-fe6b-4fad-b23a-431de1616f42 · inbound

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics cites this paper.

Sparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics Interpretable Machine Learning in Physics: A Review

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-06-27T11:00:50.727840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b9c46d4d-e998-4e6f-a117-1c069f889166 · inbound

The Ramanujan Challenge For AI cites this paper.

The Ramanujan Challenge For AI Interpretable Machine Learning in Physics: A Review

Reference 150

Resolution: unresolved; no resolver link, observed 2026-07-14T17:09:09.167784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da8749b1-34d9-4616-bea2-3b8c65f55886 · inbound

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model cites this paper.

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model Interpretable Machine Learning in Physics: A Review

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T12:55:22.304868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cecf1bb6-3457-4a38-ab33-624d133bd458 · inbound

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model cites this paper.

Interpreting learning dynamics of autoencoders: Transient scaling and emerging concepts of the Ising model Interpretable Machine Learning in Physics: A Review

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T07:23:56.728119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a44499c5-e1c7-4a0c-9f58-0d00bceb7e7c · inbound

Can AI Follow In Einstein's Footsteps? cites this paper.

Can AI Follow In Einstein's Footsteps? Interpretable Machine Learning in Physics: A Review

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-01T01:19:20.478753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.