Paper Citation Record · LEDGER

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning

As of 19 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:2501.19281.

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

pith.paper-citation-record.v1
2501.19281 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T20:47:40.701033Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T07:12:21.293282Z

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

12 of 12 outbound references displayed

verified exact1
verified fuzzy0
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation cd002fed-ef04-43b1-8940-c9946c662d6c · outbound

This paper cites Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.675318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aff180b7-9778-4c6f-8d34-cc4fcea01b31 · outbound

This paper cites Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Feature Learning in Deep Neural Networks - Studies on Speech Recognition Tasks

Reference 296

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.701033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a7b4802-887e-468f-94a9-3ab6b72fc139 · outbound

This paper cites Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks

Reference 362

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.693178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4abda10f-d860-4fa4-9284-8598d75eb289 · outbound

This paper cites [AGS87] Daniel J Amit, Hanoch Gutfreund, and Haim Sompolinsky.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning [AGS87] Daniel J Amit, Hanoch Gutfreund, and Haim Sompolinsky

Reference 1530

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.653239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbd9e003-c228-459a-bb3f-8bfca07e0bdb · outbound

This paper cites url: https ://www.sciencedirect.com/science/article/pii/0047259X83900192.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning url: https ://www.sciencedirect.com/science/article/pii/0047259X83900192

Reference 1983

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.662035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da09dd8c-4a29-408f-8703-d75fd28ca14e · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Explaining and Harnessing Adversarial Examples

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.679879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07d56dc9-4523-4211-a7c7-128a1a78d209 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.697130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4b41658-556c-47d9-90ab-8ef9a2cb9b2e · outbound

This paper cites Deep Neural Networks as Gaussian Processes.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Deep Neural Networks as Gaussian Processes

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.684251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c235f9e-0e8e-4d4b-a760-69c98252c991 · outbound

This paper cites url: https://link.aps.org/ doi/10.1103/PhysRevX.8.031003.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning url: https://link.aps.org/ doi/10.1103/PhysRevX.8.031003

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.670322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca815033-a176-4b10-be75-c823562a008e · outbound

This paper cites Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples

Reference 2019

Resolution: metadata mismatch; local_arxiv, observed 2026-08-09T20:47:41.078115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 07acc972-d739-4ca6-9174-83ae57525ee9 · outbound

This paper cites A Closer Look at Memorization in Deep Networks.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning A Closer Look at Memorization in Deep Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T20:47:40.657531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c047a3f9-f7bc-49b0-a0bf-44aada2c7250 · outbound

This paper cites url: https://link.aps.

Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning url: https://link.aps

Reference 2021

Resolution: verified exact; raw_fallback, observed 2026-08-09T20:47:41.024793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 9985edb4-6803-427d-9628-072ca1ce058f · inbound

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures cites this paper.

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures Statistical Physics of Deep Neural Networks: Generalization Capability, Beyond the Infinite Width, and Feature Learning

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:14:20.437985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.