Paper Citation Record · LEDGER

A Probabilistic Representation of Deep Learning

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:1908.09772.

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

pith.paper-citation-record.v1
1908.09772 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T11:10:39.510929Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

40 of 40 outbound references displayed

verified exact0
verified fuzzy22
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 859053b7-847c-4593-ad51-df25b15a80c5 · outbound

This paper cites Emergence of Invariance and Disentanglement in Deep Representations.

A Probabilistic Representation of Deep Learning Emergence of Invariance and Disentanglement in Deep Representations

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.344749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35f98708-2cc7-4f4c-9acc-3359eb81710b · outbound

This paper cites Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks.

A Probabilistic Representation of Deep Learning Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-08-14T11:10:39.632488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c1984f1b-7a2c-40b7-9a18-adb27b453643 · outbound

This paper cites Representation learning: A review and new perspectives.IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798–1828, 2013.

A Probabilistic Representation of Deep Learning Representation learning: A review and new perspectives.IEEE Transactions on Pattern Analysis and Machine Intelligence, 35(8):1798–1828, 2013

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.354466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c9f55e2-f5c0-4d6e-adb3-9bd70a132c64 · outbound

This paper cites Variational inference: A review for statisticians.Journal of Machine Learning Research, 112:859–877, 2017.

A Probabilistic Representation of Deep Learning Variational inference: A review for statisticians.Journal of Machine Learning Research, 112:859–877, 2017

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:40.067853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eac33054-4519-440e-a1c0-218c3aa84ba1 · outbound

This paper cites Stability and generalization.Journal of Machine Learning Research, pages 499–526, 2002.

A Probabilistic Representation of Deep Learning Stability and generalization.Journal of Machine Learning Research, pages 499–526, 2002

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:40.053577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 68a94992-c3b5-4592-bd37-383d54001284 · outbound

This paper cites Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters.

A Probabilistic Representation of Deep Learning Training stochastic model recognition algorithms as networks can lead to maximum mutual information estimation of parameters

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:40.038398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c6d71125-3f2b-4756-b1df-7e2f3519e381 · outbound

This paper cites Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks.

A Probabilistic Representation of Deep Learning Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:40.024099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 05999d27-3d9c-422b-8495-c8b54854c819 · outbound

This paper cites Wiley- Interscience, Hoboken, New Jersy, 2006.

A Probabilistic Representation of Deep Learning Wiley- Interscience, Hoboken, New Jersy, 2006

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:40.009866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6bb7733a-e31c-4470-8748-30fd0040118c · outbound

This paper cites Geman and D.

A Probabilistic Representation of Deep Learning Geman and D

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.994480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 707b26a3-41d1-4901-9bee-47a2206e2457 · outbound

This paper cites A probabilistic approach to the understanding and training of neural network classiﬁers.

A Probabilistic Representation of Deep Learning A probabilistic approach to the understanding and training of neural network classiﬁers

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.980349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 27eb6335-7ba0-4cc3-8a8a-279392820025 · outbound

This paper cites MIT Press, 2016.

A Probabilistic Representation of Deep Learning MIT Press, 2016

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.387962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fd9e69c-9398-414f-9e68-22002dbbe6ae · outbound

This paper cites Lawrence.

A Probabilistic Representation of Deep Learning Lawrence

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.957638Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bec56d51-7206-4c5d-bcc4-a35c029dfbe4 · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.944063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 84f3d0de-1f61-4957-83c6-4fc39e824744 · outbound

This paper cites Hoﬀman, David M.

A Probabilistic Representation of Deep Learning Hoﬀman, David M

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.930862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation edcc564e-b78f-4051-a95b-9d3c42af2300 · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 15

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.917391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41afecdc-93e3-4c63-8d12-816c0904cdec · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.905343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8b0f309f-a079-4649-b2de-dd0d15c09401 · outbound

This paper cites MIT Press, 2006.

A Probabilistic Representation of Deep Learning MIT Press, 2006

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.892366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ddd6d887-9abe-4db2-879b-13db87610388 · outbound

This paper cites A bayesian hierarchical model for learning natural scene categories.

A Probabilistic Representation of Deep Learning A bayesian hierarchical model for learning natural scene categories

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.879089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8e90bd15-75a8-432c-8a19-87ddd3ea3b71 · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.866383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 21511726-3b28-4e2a-b4e2-61b5b926bc26 · outbound

This paper cites An exact mapping between the Variational Renormalization Group and Deep Learning.

A Probabilistic Representation of Deep Learning An exact mapping between the Variational Renormalization Group and Deep Learning

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.426031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0729cae-cbb5-4fd7-bd28-7fdc803bd22e · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.854057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1d090719-6a6c-47e1-ae52-0311cac12e88 · outbound

This paper cites Deep Learning and the Information Bottleneck Principle.

A Probabilistic Representation of Deep Learning Deep Learning and the Information Bottleneck Principle

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.434688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2aa777d5-5511-4f26-9977-b5af132ad8df · outbound

This paper cites Exploring generalization in deep learning.

A Probabilistic Representation of Deep Learning Exploring generalization in deep learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.840102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7b4d8889-10fd-4c5e-be0b-9c6ff4c7bf5e · outbound

This paper cites In search of the real inductive bias: On the role of implicit regularization in deep learning.

A Probabilistic Representation of Deep Learning In search of the real inductive bias: On the role of implicit regularization in deep learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.827426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6a22792c-37c1-408e-a5ba-9eda90f7164b · outbound

This paper cites Ng and Michael I.

A Probabilistic Representation of Deep Learning Ng and Michael I

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.814273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 468dbdfa-5b55-4cf2-b676-77a4b96d5c50 · outbound

This paper cites Statistical exponential families: A digest with flash cards.

A Probabilistic Representation of Deep Learning Statistical exponential families: A digest with flash cards

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.451344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4cbb117-bf74-4442-97b5-22e6b41b08ea · outbound

This paper cites Aprobabilisticframework for deep learning.

A Probabilistic Representation of Deep Learning Aprobabilisticframework for deep learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.801357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d913b689-fa70-4c16-8169-70d0816d588c · outbound

This paper cites Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution.

A Probabilistic Representation of Deep Learning Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.460022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 232f9aae-af9b-4fed-898d-e9a65ebb2756 · outbound

This paper cites Richard and R.P.

A Probabilistic Representation of Deep Learning Richard and R.P

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.788416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1cfa1785-8f6b-494e-bc5a-96ad2450f46c · outbound

This paper cites Rumelhart, Geoﬀrey E.

A Probabilistic Representation of Deep Learning Rumelhart, Geoﬀrey E

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.775011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation efcfc163-628b-4b05-b2fd-f5905126f79c · outbound

This paper cites Deep boltzmann machines.

A Probabilistic Representation of Deep Learning Deep boltzmann machines

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.760385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 98462bf6-7f62-4325-a2e7-fa807dd99899 · outbound

This paper cites On the information bottleneck theory of deep learning.

A Probabilistic Representation of Deep Learning On the information bottleneck theory of deep learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.746590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d02adc9f-2995-4e6c-9867-261508277f69 · outbound

This paper cites Opening the Black Box of Deep Neural Networks via Information.

A Probabilistic Representation of Deep Learning Opening the Black Box of Deep Neural Networks via Information

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.482581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3abe59eb-f634-49ba-af34-ad691ccca99e · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.732110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11e6bda5-88f1-4ad1-beff-bc7d26747187 · outbound

This paper cites Jaakkola.

A Probabilistic Representation of Deep Learning Jaakkola

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.716765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ea8e7ab-7fef-4fe1-94ab-352644b1ecb3 · outbound

This paper cites Deep Mixtures of Factor Analysers.

A Probabilistic Representation of Deep Learning Deep Mixtures of Factor Analysers

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T11:10:39.494696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bd05c9b-063c-4be2-87f5-f4593e5e0440 · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.702803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1237d842-c587-4674-a973-0c8993e2c991 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

A Probabilistic Representation of Deep Learning Understanding deep learning requires rethinking generalization

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.688888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0c0ce6b6-8b7e-4493-98f6-dbbfc3590b17 · outbound

This paper cites an unresolved cited work.

A Probabilistic Representation of Deep Learning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-14T11:10:39.675164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 57e49a3b-8b60-4929-b741-7c70c93abd0a · outbound

This paper cites Conditional random ﬁelds as recurrent neural networks.

A Probabilistic Representation of Deep Learning Conditional random ﬁelds as recurrent neural networks

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T11:10:39.661847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.