Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T02:50:06.746659Z
Paper Citation Record · LEDGER
Width-Robust Learnability in Mean-Field Bayesian Neural Networks
As of 7 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.