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Paper Citation Record · LEDGER

Large deviation principles for convolutional Bayesian neural networks

As of 13 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2603.06023.

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

pith.paper-citation-record.v1
2603.06023 v2

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-15T14:03:39.869199Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1f1916fd-7add-4951-87ab-c535e8977124 · outbound

This paper cites Aiudi, R.

Large deviation principles for convolutional Bayesian neural networks Aiudi, R

Reference 1

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Observation a290b135-6252-4741-ac01-a37d25bb23d2 · outbound

This paper cites Andreis, F.

Large deviation principles for convolutional Bayesian neural networks Andreis, F

Reference 2

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Observation 6f44696c-3071-47d7-8373-8606b80838d6 · outbound

This paper cites Baglioni, R.

Large deviation principles for convolutional Bayesian neural networks Baglioni, R

Reference 3

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Observation a96e1a70-a7fa-46f0-86d6-50d78a46b783 · outbound

This paper cites Proportional infinite-width infinite-depth limit for deep linear neural networks.

Large deviation principles for convolutional Bayesian neural networks Proportional infinite-width infinite-depth limit for deep linear neural networks

Reference 4

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Observation a06d1de2-8c5b-450e-b0e5-75bc0b41fea2 · outbound

This paper cites Bhatia.Matrix Analysis, volume 169 ofGraduate Texts in Mathematics.

Large deviation principles for convolutional Bayesian neural networks Bhatia.Matrix Analysis, volume 169 ofGraduate Texts in Mathematics

Reference 5

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Observation 345f900a-8ccf-4e48-b3ae-410743b43f37 · outbound

This paper cites Entropic bounds for conditionally Gaussian vectors and applications to neural networks.

Large deviation principles for convolutional Bayesian neural networks Entropic bounds for conditionally Gaussian vectors and applications to neural networks

Reference 6

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 7

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Observation 5323424e-c322-4bc2-a299-e2f450b9bd54 · outbound

This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 8

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Observation 523efd9b-a635-43bf-be75-2d873b39b0d3 · outbound

This paper cites Dembo and O.

Large deviation principles for convolutional Bayesian neural networks Dembo and O

Reference 9

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Observation 83aa43c9-b7cd-48cc-aa88-32b23461a036 · outbound

This paper cites Favaro, B.

Large deviation principles for convolutional Bayesian neural networks Favaro, B

Reference 10

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Observation 69a05001-2aa6-4516-bcd9-9f5126e96f37 · outbound

This paper cites Goodfellow, Y.

Large deviation principles for convolutional Bayesian neural networks Goodfellow, Y

Reference 11

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 12

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 13

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 14

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 15

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Observation 60c66569-645c-44f6-82c7-b77a44e4a2ad · outbound

This paper cites Macci, B.

Large deviation principles for convolutional Bayesian neural networks Macci, B

Reference 16

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Observation 5d7b7ae2-4f90-44f0-8eb1-6295c040449d · outbound

This paper cites Macci, B.

Large deviation principles for convolutional Bayesian neural networks Macci, B

Reference 17

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Observation 4b4906d2-b26c-41a8-89d2-e4bdf8685ae7 · outbound

This paper cites Novak, L.

Large deviation principles for convolutional Bayesian neural networks Novak, L

Reference 18

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Observation 936abb99-9b6e-42e5-8e5c-4cc3b017bc85 · outbound

This paper cites Pacelli, S.

Large deviation principles for convolutional Bayesian neural networks Pacelli, S

Reference 19

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Observation 9853f2f1-68a0-4b04-9e01-3aeefed7004e · outbound

This paper cites Rezakhanlou.

Large deviation principles for convolutional Bayesian neural networks Rezakhanlou

Reference 20

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Observation 567d6109-06c3-4b68-83cb-5b06c3510553 · outbound

This paper cites Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes.

Large deviation principles for convolutional Bayesian neural networks Wide Deep Neural Networks with Gaussian Weights are Very Close to Gaussian Processes

Reference 21

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Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 22

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This paper cites an unresolved cited work.

Large deviation principles for convolutional Bayesian neural networks Unresolved cited work

Reference 23

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This paper cites Yang and E.

Large deviation principles for convolutional Bayesian neural networks Yang and E

Reference 24

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Pith citing papers

No inbound Pith citation observations are available.