Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T15:36:20.103489Z
Paper Citation Record · LEDGER
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing
As of 16 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2411.14288.
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 2026-08-16T06:30:59.297886+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
21 of 21 outbound references displayed
- verified exact4
- verified fuzzy9
- unresolved8
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 199dac79-1831-4816-a89e-794f3dd86ccb · outbound
This paper cites Stronger Generalization Bounds for Deep Nets via a Compression Approach.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Stronger Generalization Bounds for Deep Nets via a Compression Approach
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.376750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 623716dd-04ff-47e9-9501-4220d3a940dc · outbound
This paper cites 2c focusing on the models training with the largest dataset sizem = 25600.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing 2c focusing on the models training with the largest dataset sizem = 25600
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.308850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation eb874e93-c9b2-4b53-81a2-52050503d673 · outbound
This paper cites Symmetries and discriminability in feedforward network architectures.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Symmetries and discriminability in feedforward network architectures
Reference 4
- Resolution
- verified exact
- raw_fallback, observed 2026-08-12T15:36:20.239810Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b329fc8b-5138-4355-9bed-b91603f223cb · outbound
This paper cites Provably strict generalisation benefit for equivariant models.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Provably strict generalisation benefit for equivariant models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.059724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 67113ff1-d0ae-4089-b498-64649d0f2f08 · outbound
This paper cites Group invariant scattering.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Group invariant scattering
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.339704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cee1c638-1bdf-4e4d-b612-118e1c5a6b3b · outbound
This paper cites In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing In Defense of Uniform Convergence: Generalization via derandomization with an application to interpolating predictors
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:36:20.260969Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 27703891-0a63-45e2-9e77-d917b04e13bd · outbound
This paper cites Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.092279Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d43d6292-030a-4be3-87f1-bee07d9f2d56 · outbound
This paper cites Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Improved Sample Complexities for Deep Networks and Robust Classification via an All-Layer Margin
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.095457Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0abfeed5-cca5-40a2-a54f-6d5f740a5cc2 · outbound
This paper cites Covering number bounds of certain regularized linear function classes.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Covering number bounds of certain regularized linear function classes
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.316980Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2776c9b5-c62f-4085-8b33-0acb37523af1 · outbound
This paper cites Non-Vacuous Generalisation Bounds for Shallow Neural Networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Non-Vacuous Generalisation Bounds for Shallow Neural Networks
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:36:20.300703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d8552db8-1331-4f23-98a8-a8718335b2bc · outbound
This paper cites A functional approach to rotation equivariant non-linearities for Tensor Field Networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing A functional approach to rotation equivariant non-linearities for Tensor Field Networks
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.332322Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f594d360-18c9-45ab-93b9-ee0707e81f5b · outbound
This paper cites A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing A practical method for constructing equivariant multilayer perceptrons for arbitrary matrix groups
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.354114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d02a7548-7f5f-432a-8549-5d91d6e1832d · outbound
This paper cites Dynamic routing between capsules.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Dynamic routing between capsules
Reference 1977
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.324420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7adce3e0-288f-4955-a8c4-cc13fec9a317 · outbound
This paper cites The role of invariance in spectral complexity-based generalization bounds.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing The role of invariance in spectral complexity-based generalization bounds
Reference 1989
- Resolution
- verified exact
- local_arxiv, observed 2026-08-12T15:36:20.249855Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 67d0d8cb-ca07-42ea-97d1-4af1f55149e0 · outbound
This paper cites On the Benefits of Invariance in Neural Networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing On the Benefits of Invariance in Neural Networks
Reference 2011
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.070947Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53e120c2-2435-4385-9cbd-1fe6c055543c · outbound
This paper cites Theoretical Analysis of Inductive Biases in Deep Convolutional Networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Theoretical Analysis of Inductive Biases in Deep Convolutional Networks
Reference 2017
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.098137Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae25e59d-356f-4fc7-a805-13ad8e904755 · outbound
This paper cites Generalization bounds for deep convolutional neural networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Generalization bounds for deep convolutional neural networks
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.067992Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f2ec5a2e-55ea-454a-9a3a-a6dcfe67b189 · outbound
This paper cites Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.053482Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5943d167-696c-4a42-a463-2c0f7c08cbc4 · outbound
This paper cites On the generalization of equivariance and convolution in neural networks to the action of compact groups.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing On the generalization of equivariance and convolution in neural networks to the action of compact groups
Reference 2021
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.346693Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4821418a-ea13-47de-af68-fa2b7006bc8e · outbound
This paper cites Group Equivariant Convolutional Networks.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Group Equivariant Convolutional Networks
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T15:36:20.050365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49259aea-b60c-4bf4-9395-0a8111a2d313 · outbound
This paper cites Uncertainty Principles and Signal Recovery.
On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Uncertainty Principles and Signal Recovery
Reference 8441
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T15:36:20.367523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.