Paper Citation Record · LEDGER

Variational Inference for Latent Variable Models in High Dimensions

As of 8 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 1 inbound Pith citation observation for arXiv:2506.01893.

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

pith.paper-citation-record.v1
2506.01893 v2

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

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External citation measurements

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Outbound references

Observation 00e1ac81-29f9-47fa-97c6-2921c8a4b00e · outbound

This paper cites write newline.

Variational Inference for Latent Variable Models in High Dimensions write newline

Reference 1

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This paper cites ( 2018 ).

Variational Inference for Latent Variable Models in High Dimensions ( 2018 )

Reference 2

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Variational Inference for Latent Variable Models in High Dimensions Unresolved cited work

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Reference 4

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This paper cites , Ridgway , James J.

Variational Inference for Latent Variable Models in High Dimensions , Ridgway , James J

Reference 5

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This paper cites Convergence of coordinate ascent variational inference for log-concave measures via optimal transport.

Variational Inference for Latent Variable Models in High Dimensions Convergence of coordinate ascent variational inference for log-concave measures via optimal transport

Reference 6

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This paper cites ( 2021 ).

Variational Inference for Latent Variable Models in High Dimensions ( 2021 )

Reference 7

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Variational Inference for Latent Variable Models in High Dimensions , Pati , Debdeep D

Reference 8

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This paper cites , Choi , David D.

Variational Inference for Latent Variable Models in High Dimensions , Choi , David D

Reference 9

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Variational Inference for Latent Variable Models in High Dimensions , Bunea , Florentina F

Reference 10

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Variational Inference for Latent Variable Models in High Dimensions Unresolved cited work

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This paper cites A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression.

Variational Inference for Latent Variable Models in High Dimensions A variational Bayes approach to debiased inference for low-dimensional parameters in high-dimensional linear regression

Reference 15

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This paper cites Dembo , Amir A.

Variational Inference for Latent Variable Models in High Dimensions Dembo , Amir A

Reference 16

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Variational Inference for Latent Variable Models in High Dimensions , Handschy , Madeline M

Reference 17

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Variational Inference for Latent Variable Models in High Dimensions Rigon , Tommaso T

Reference 20

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Variational Inference for Latent Variable Models in High Dimensions ( 2018 )

Reference 21

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Variational Inference for Latent Variable Models in High Dimensions , Stephens , Matthew M

Reference 22

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This paper cites Gradient flows for empirical Bayes in high-dimensional linear models.

Variational Inference for Latent Variable Models in High Dimensions Gradient flows for empirical Bayes in high-dimensional linear models

Reference 23

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Variational Inference for Latent Variable Models in High Dimensions , Boyles , Levi L

Reference 24

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Variational Inference for Latent Variable Models in High Dimensions , Ma , Zongming Z

Reference 25

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Variational Inference for Latent Variable Models in High Dimensions Klopp , Olga O

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Variational Inference for Latent Variable Models in High Dimensions , Javadi , Hamid H

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Variational Inference for Latent Variable Models in High Dimensions Dunson , David B D

Reference 29

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Variational Inference for Latent Variable Models in High Dimensions ( 1982 )

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Variational Inference for Latent Variable Models in High Dimensions , Liu , Yan Y

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Variational Inference for Latent Variable Models in High Dimensions , Wang , Wei W

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Variational Inference for Latent Variable Models in High Dimensions Zanella , Giacomo G

Reference 37

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Variational Inference for Latent Variable Models in High Dimensions Rinaldo , Alessandro A

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Variational Inference for Latent Variable Models in High Dimensions , Moss , Fabian C F

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Variational Inference for Latent Variable Models in High Dimensions On Naive Mean-Field Approximation for high-dimensional canonical GLMs

Reference 40

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Variational Inference for Latent Variable Models in High Dimensions A Mean Field Approach to Empirical Bayes Estimation in High-dimensional Linear Regression

Reference 41

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Variational Inference for Latent Variable Models in High Dimensions Sen , Subhabrata S

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Variational Inference for Latent Variable Models in High Dimensions , Bhattacharya , Anirban A

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Variational Inference for Latent Variable Models in High Dimensions Szab \'o , Botond B

Reference 46

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Variational Inference for Latent Variable Models in High Dimensions , Chu , Jing J

Reference 49

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Variational Inference for Latent Variable Models in High Dimensions ( 2014 )

Reference 51

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Variational Inference for Latent Variable Models in High Dimensions Kumar , Sathish AP S

Reference 52

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This paper cites Blei , David M D.

Variational Inference for Latent Variable Models in High Dimensions Blei , David M D

Reference 54

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Variational Inference for Latent Variable Models in High Dimensions , Yang , Wen W

Reference 55

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This paper cites Blei , David M D.

Variational Inference for Latent Variable Models in High Dimensions Blei , David M D

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Variational Inference for Latent Variable Models in High Dimensions Gao , Chao C

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Variational Bayes and Truncation approximations for Enriched Dirichlet process mixtures Variational Inference for Latent Variable Models in High Dimensions

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