Paper Citation Record · LEDGER

Finite size corrections for neural network Gaussian processes

As of 17 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 1 inbound Pith citation observation for arXiv:1908.10030.

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

pith.paper-citation-record.v1
1908.10030 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:02:29.386424Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T15:16:43.188809Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T15:34:48.727183Z

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy2
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2b8dcff3-2545-45ad-a1fd-a99fc8f50098 · outbound

This paper cites Gaussian Process Behaviour in Wide Deep Neural Networks.

Finite size corrections for neural network Gaussian processes Gaussian Process Behaviour in Wide Deep Neural Networks

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.367914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc045f87-5fd5-4cbb-9104-d43931982178 · outbound

This paper cites Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A.

Finite size corrections for neural network Gaussian processes Paszke, A., Gross, S., Chintala, S., Chanan, G., Yang, E., DeVito, Z., Lin, Z., Desmaison, A., Antiga, L., and Lerer, A

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:29.581638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 77528861-54cc-4081-b6ed-9be06bfc629b · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Finite size corrections for neural network Gaussian processes EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.381444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 530ab907-c619-4a97-b971-1aae9b46c018 · outbound

This paper cites an unresolved cited work.

Finite size corrections for neural network Gaussian processes Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:02:29.565107Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6350363c-1f53-4a43-88b8-93ea159717b3 · outbound

This paper cites Deep Convolutional Networks as shallow Gaussian Processes.

Finite size corrections for neural network Gaussian processes Deep Convolutional Networks as shallow Gaussian Processes

Reference 1966

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.336909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6745b5e-95d9-4a74-b452-bc74ba80a51e · outbound

This paper cites Deep Neural Networks as Gaussian Processes.

Finite size corrections for neural network Gaussian processes Deep Neural Networks as Gaussian Processes

Reference 1995

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.358456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6715b100-e766-42e0-ae99-670aa5631650 · outbound

This paper cites S., Hu, W., Li, Z., Salakhutdinov, R., and Ruosong, W.

Finite size corrections for neural network Gaussian processes S., Hu, W., Li, Z., Salakhutdinov, R., and Ruosong, W

Reference 1999

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:02:29.596383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 97507fce-c8f9-4496-8f54-5c2d9db55132 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Finite size corrections for neural network Gaussian processes Distilling the Knowledge in a Neural Network

Reference 2006

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.342347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2b6b1d6-6883-4232-ac4a-eaa08b932dd5 · outbound

This paper cites Searching for MobileNetV3.

Finite size corrections for neural network Gaussian processes Searching for MobileNetV3

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.347682Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a451b1ed-81d9-4611-bc66-04cc96959125 · outbound

This paper cites Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent.

Finite size corrections for neural network Gaussian processes Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.363232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3aa6a6e5-d4a6-47ad-9cbe-a30046ee0c05 · outbound

This paper cites Exact solutions to the nonlinear dynamics of learning in deep linear neural networks.

Finite size corrections for neural network Gaussian processes Exact solutions to the nonlinear dynamics of learning in deep linear neural networks

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.376595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 551fa727-18d3-489a-82e2-a7ad034ce08a · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Finite size corrections for neural network Gaussian processes MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-14T11:02:29.353217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 2a562652-6878-4cf6-a729-5bc69840976a · inbound

Optimal Non-Asymptotic Edgeworth Expansions for Multivariate Neural Network Outputs cites this paper.

Optimal Non-Asymptotic Edgeworth Expansions for Multivariate Neural Network Outputs Finite size corrections for neural network Gaussian processes

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:48.728512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.