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Paper Citation Record · LEDGER

An Introduction to Discrete Variational Autoencoders

As of 18 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.10344.

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

pith.paper-citation-record.v1
2505.10344 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:15:03.158816Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

23 of 23 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved11
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f3d9b499-0885-49b7-be9d-104fbf2367f8 · outbound

This paper cites Deep learning: Foundations and concepts.

An Introduction to Discrete Variational Autoencoders Deep learning: Foundations and concepts

Reference 1

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a7fb98bf-6c41-4cd0-be09-9532ee4a8a47 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

An Introduction to Discrete Variational Autoencoders Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 2

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no resolver link, observed 2026-08-15T21:15:03.078792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:15:03.078792Z digest=sha256:d591ef81ee0cdbd15e2bbabcd6bacc5d0e029aa6c7902803ed1acc4b7197bb6d

Observation d3cb1520-dfa8-48dd-b6d9-b7ec9755e6b0 · outbound

This paper cites The helmholtz machine.

An Introduction to Discrete Variational Autoencoders The helmholtz machine

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 70e18231-7b47-4e88-8c39-4de16d192269 · outbound

This paper cites Tutorial on Variational Autoencoders.

An Introduction to Discrete Variational Autoencoders Tutorial on Variational Autoencoders

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8183cc26-20ca-44f6-9471-0daefe6e6a8f · outbound

This paper cites Backpropagation through the void: Optimizing control variates for black-box gradient estimation.

An Introduction to Discrete Variational Autoencoders Backpropagation through the void: Optimizing control variates for black-box gradient estimation

Reference 5

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 269255be-409a-4d28-8deb-265a4491a5e4 · outbound

This paper cites Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey.

An Introduction to Discrete Variational Autoencoders Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey

Reference 6

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no resolver link, observed 2026-08-15T21:15:03.095597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 855e52c7-8cd7-4d84-8069-646a9c45aec7 · outbound

This paper cites Scaling and evaluating sparse autoencoders.

An Introduction to Discrete Variational Autoencoders Scaling and evaluating sparse autoencoders

Reference 7

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no resolver link, observed 2026-08-15T21:15:03.099707Z

Source-reported events for the cited work

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Observation 3fc901ce-dde9-4154-8b96-9ecda25456b4 · outbound

This paper cites Categorical reparameterization with gumbel-softmax.

An Introduction to Discrete Variational Autoencoders Categorical reparameterization with gumbel-softmax

Reference 8

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no resolver link, observed 2026-08-15T21:15:03.104102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:15:03.104102Z digest=sha256:1c55b47b5277faa83cbca43522a24b024858969d5337b282c82ca14a917d7867

Observation 1aafdc75-eae8-449c-9e5a-d95ae97b268e · outbound

This paper cites Nonlinear principal component analysis using autoassociative neural networks.

An Introduction to Discrete Variational Autoencoders Nonlinear principal component analysis using autoassociative neural networks

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 72e1da95-1dec-4696-98a8-9bf2b6bad10f · outbound

This paper cites Kingma and Max Welling.

An Introduction to Discrete Variational Autoencoders Kingma and Max Welling

Reference 10

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no resolver link, observed 2026-08-15T21:15:03.111315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 103db04e-7322-4f87-ac5f-81367c8060f0 · outbound

This paper cites An introduction to variational autoencoders.

An Introduction to Discrete Variational Autoencoders An introduction to variational autoencoders

Reference 11

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 05965eca-ffb1-40bf-a15e-cd38a390d37b · outbound

This paper cites Bridging discrete and backpropagation: Straight-through and beyond.

An Introduction to Discrete Variational Autoencoders Bridging discrete and backpropagation: Straight-through and beyond

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b6d7e2b3-44eb-4672-b733-366113958054 · outbound

This paper cites The continuous bernoulli: fixing a pervasive error in variational autoencoders.

An Introduction to Discrete Variational Autoencoders The continuous bernoulli: fixing a pervasive error in variational autoencoders

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-15T21:15:03.332240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0f25f10d-1fbe-4e3f-85d5-913874120907 · outbound

This paper cites GRIN: GRadient-INformed MoE.

An Introduction to Discrete Variational Autoencoders GRIN: GRadient-INformed MoE

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d560bcbe-252a-4278-9ae0-52bfc55efc35 · outbound

This paper cites Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2.

An Introduction to Discrete Variational Autoencoders Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2

Reference 15

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no resolver link, observed 2026-08-15T21:15:03.128731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d97e386a-944a-49b9-8088-e1c07713c501 · outbound

This paper cites Probabilistic machine learning: Advanced topics.

An Introduction to Discrete Variational Autoencoders Probabilistic machine learning: Advanced topics

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-15T21:15:03.321243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0a23cd0c-33d4-4f2b-b438-f98f0b0ce57b · outbound

This paper cites Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function.

An Introduction to Discrete Variational Autoencoders Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function

Reference 17

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no resolver link, observed 2026-08-15T21:15:03.135967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7088ddb7-da15-4b55-b303-a663db2d57f8 · outbound

This paper cites Understanding deep learning.

An Introduction to Discrete Variational Autoencoders Understanding deep learning

Reference 18

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 199cd8e9-74d5-4ddd-b412-8ffabc72d651 · outbound

This paper cites Stochastic backpropagation and approximate inference in deep generative models.

An Introduction to Discrete Variational Autoencoders Stochastic backpropagation and approximate inference in deep generative models

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4383a566-07fa-4ccd-a46a-719c1451003f · outbound

This paper cites Discrete variational autoencoders.

An Introduction to Discrete Variational Autoencoders Discrete variational autoencoders

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation b23ce0a4-0b94-4c14-af92-1f7a7db73c23 · outbound

This paper cites Generating diverse high-fidelity images with vq-vae-2.

An Introduction to Discrete Variational Autoencoders Generating diverse high-fidelity images with vq-vae-2

Reference 21

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no resolver link, observed 2026-08-15T21:15:03.150860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 15e356cf-5c4c-45c2-8ae1-9d5119347b88 · outbound

This paper cites Neural discrete representation learning.

An Introduction to Discrete Variational Autoencoders Neural discrete representation learning

Reference 22

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b422cfdd-57d4-4d30-9744-7b19793f01f0 · outbound

This paper cites Dvae++: Discrete variational autoencoders with overlapping transformations.

An Introduction to Discrete Variational Autoencoders Dvae++: Discrete variational autoencoders with overlapping transformations

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Pith citing papers

No inbound Pith citation observations are available.