Paper Citation Record · LEDGER

Width-Robust Learnability in Mean-Field Bayesian Neural Networks

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.05735.

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

pith.paper-citation-record.v1
2607.05735 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T02:50:06.746659Z

measured 24 of 24 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

verified exact5
verified fuzzy17
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f441e539-48f4-4105-b77d-c61cb0533f99 · outbound

This paper cites Edelman, Surbhi Goel, Sham Kakade, Eran Malach, and Cyril Zhang.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Edelman, Surbhi Goel, Sham Kakade, Eran Malach, and Cyril Zhang

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.799529Z

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 ca1051ac-b4f0-4a95-a2e5-c8519acb4232 · outbound

This paper cites Self-consistent dynamical field theory of kernel evo- lution in wide neural networks.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Self-consistent dynamical field theory of kernel evo- lution in wide neural networks

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.866066Z

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 6b153374-63aa-4ea5-9032-63e169a31f8c · outbound

This paper cites How uniform random weights induce non-uniform bias: Typical interpolating neural networks generalize with narrow teachers.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks How uniform random weights induce non-uniform bias: Typical interpolating neural networks generalize with narrow teachers

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.575860Z

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 3b3983f4-9f2d-453c-b0d7-cecf043201ac · outbound

This paper cites an unresolved cited work.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-07-11T02:57:56.609984Z

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 f0a04536-1a7d-4ed7-8d32-64e7464c5fbe · outbound

This paper cites Generalization bounds for neural networks via approximate description length.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Generalization bounds for neural networks via approximate description length

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.704442Z

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 e24aba7a-6c60-455d-82c0-4fc1a7065c4a · outbound

This paper cites On the sample complexity of two-layer networks: Lipschitz vs.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks On the sample complexity of two-layer networks: Lipschitz vs

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.831828Z

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 1e81abbe-8e26-407c-ac3d-08587aa9a706 · outbound

This paper cites Learning parities with neural networks.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Learning parities with neural networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.542913Z

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 1dda7ac2-3187-48fc-9b6f-e38505af4efd · outbound

This paper cites Algorithmic Task Capture, Computational Complexity, and Inductive Bias of Infinite Transformers.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Algorithmic Task Capture, Computational Complexity, and Inductive Bias of Infinite Transformers

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-11T02:57:47.089470Z

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 fd3f3efd-55df-498b-880b-341a1463cc19 · outbound

This paper cites Lecture notes: From gaussian processes to feature learning.arXiv preprint arXiv:2602.12855, 2026.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Lecture notes: From gaussian processes to feature learning.arXiv preprint arXiv:2602.12855, 2026

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-11T02:57:47.052198Z

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 0617aac7-55fe-4d2d-a6bd-204e2959f514 · outbound

This paper cites Neuraltangentkernel: convergenceand generalization in neural networks.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Neuraltangentkernel: convergenceand generalization in neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.641731Z

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 5a8e3961-d350-466d-b79a-a55f4d0c37ce · outbound

This paper cites Adaptive kernel predictors from feature-learning infinite limits of neural networks.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Adaptive kernel predictors from feature-learning infinite limits of neural networks

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-07-11T02:57:47.204069Z

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 f1486a1a-10e9-4285-8029-1ab76da74272 · outbound

This paper cites Schoenholz, Jeffrey Pennington, and Jascha Sohl-Dickstein.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Schoenholz, Jeffrey Pennington, and Jascha Sohl-Dickstein

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.486555Z

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 95f82985-87fb-4d4e-a0c6-eb09d19f4adb · outbound

This paper cites Lin, Allan Pinkus, and Shimon Schocken.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Lin, Allan Pinkus, and Shimon Schocken

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.514285Z

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 9ff6274a-921b-446f-95c8-483d2c00bc49 · outbound

This paper cites A mean field view of the landscape of two-layer neural networks.Proceedings of the National Academy of Sciences of the United States of America, 115:E7665 – E7671, 2018.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks A mean field view of the landscape of two-layer neural networks.Proceedings of the National Academy of Sciences of the United States of America, 115:E7665 – E7671, 2018

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.425089Z

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 ef932345-35cc-4385-8ba5-302153135159 · outbound

This paper cites A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-07-11T02:57:47.166961Z

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 1856196e-329d-4d1b-b1c2-5a414cf705cc · outbound

This paper cites A rigorous framework for the mean field limit of multilayer neural networks.Mathematical Statistics and Learning, 6(3):201–357, 2023.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks A rigorous framework for the mean field limit of multilayer neural networks.Mathematical Statistics and Learning, 6(3):201–357, 2023

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.670256Z

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 8da0fc37-deab-47fc-8fe3-74611ebe613f · outbound

This paper cites Rotskoff and Eric Vanden-Eijnden.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Rotskoff and Eric Vanden-Eijnden

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.455604Z

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 3a6c8c29-14f9-41ec-9f34-7bd223e50be3 · outbound

This paper cites Mitigating the curse of detail: Scaling arguments for feature learning and sample complexity.arXiv preprint arXiv:2512.04165, 2025.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Mitigating the curse of detail: Scaling arguments for feature learning and sample complexity.arXiv preprint arXiv:2512.04165, 2025

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-11T02:57:47.125716Z

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 eed3d484-6cde-431a-95ee-da4fb7f9ee03 · outbound

This paper cites From kernels to features: A multi-scale adaptive theory of feature learning.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks From kernels to features: A multi-scale adaptive theory of feature learning

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.366195Z

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 8daded67-2b82-4fdf-bece-efa56dcfed85 · outbound

This paper cites A unified approach to fea- ture learning in bayesian neural networks.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks A unified approach to fea- ture learning in bayesian neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.766846Z

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 d1c6ced4-3de4-4bd0-8c15-6b2318d47611 · outbound

This paper cites Separation of scales and a thermodynamic description of feature learning in some cnns.Nature Communications, 14, 2021.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Separation of scales and a thermodynamic description of feature learning in some cnns.Nature Communications, 14, 2021

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.330167Z

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 2ec23183-bbd0-45cc-82ea-11d5b1fc38fa · outbound

This paper cites Sirignano and Konstantinos V.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Sirignano and Konstantinos V

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.731102Z

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 e6a115e9-b312-4aa9-9ed5-6d6bf54af367 · outbound

This paper cites Edward Hu.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Edward Hu

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-11T02:57:56.396406Z

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 81dda550-f4a4-431b-9622-6c14dd890e1c · outbound

This paper cites Summary statistics of learning link changing neural representations to behavior.

Width-Robust Learnability in Mean-Field Bayesian Neural Networks Summary statistics of learning link changing neural representations to behavior

Reference 24

Resolution: metadata mismatch; local_arxiv, observed 2026-07-11T02:57:47.236988Z

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.

Pith citing papers

No inbound Pith citation observations are available.