Paper Citation Record · LEDGER

Fixed point actions from convolutional neural networks

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.17816.

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

pith.paper-citation-record.v1
2311.17816 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:15:54.374528Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T23:45:07.434541Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
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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 60209073-e169-4302-9a37-f95f0b148389 · inbound

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics cites this paper.

Physics-Driven Learning for Inverse Problems in Quantum Chromodynamics Fixed point actions from convolutional neural networks

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:15:54.374528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b614e476-becf-4f26-8795-663a1410c43f · inbound

HMC and gradient flow with machine-learned classically perfect fixed-point actions cites this paper.

HMC and gradient flow with machine-learned classically perfect fixed-point actions Fixed point actions from convolutional neural networks

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T05:15:04.336409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93633a37-5717-48ad-868e-daa1de6fbd28 · inbound

Machine learning for four-dimensional SU(3) lattice gauge theories cites this paper.

Machine learning for four-dimensional SU(3) lattice gauge theories Fixed point actions from convolutional neural networks

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:25:29.551539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 93fbf57c-8c75-4d86-b68e-8d1fc479e2b4 · inbound

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions cites this paper.

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions Fixed point actions from convolutional neural networks

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:01:11.517817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d809bd32-fd06-4437-8252-4ef1f0fa7af7 · inbound

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions cites this paper.

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions Fixed point actions from convolutional neural networks

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:08:04.061189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 092909f9-8acc-4645-90c3-4f507eafd9ec · inbound

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions cites this paper.

Lattice fermion formulation via Physics-Informed Neural Networks: Ginsparg-Wilson relation and Overlap fermions Fixed point actions from convolutional neural networks

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-30T23:45:07.436895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.