Paper Citation Record · LEDGER

Adversarial Dependence Minimization

As of 10 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 1 inbound Pith citation observation for arXiv:2502.03227.

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

pith.paper-citation-record.v1
2502.03227 v2

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:33:45.232723Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T04:08:14.195239Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

71 of 71 outbound references displayed

verified exact2
verified fuzzy23
unresolved46
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b6b8ffe5-5fc7-431a-bbb8-9432e89948b8 · outbound

This paper cites write newline.

Adversarial Dependence Minimization write newline

Reference 1

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Observation 816415a3-b3a2-4128-955a-999c7fc9c93a · outbound

This paper cites an unresolved cited work.

Adversarial Dependence Minimization Unresolved cited work

Reference 2

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Observation d5c09588-323e-4141-8e75-a328b9aa5ba3 · outbound

This paper cites and Hornik, K.

Adversarial Dependence Minimization and Hornik, K

Reference 3

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Observation fa31eb04-9187-4dda-b704-8f78af7c72f2 · outbound

This paper cites Vicreg: Variance-invariance-covariance regularization for self-supervised learning.

Adversarial Dependence Minimization Vicreg: Variance-invariance-covariance regularization for self-supervised learning

Reference 4

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Observation 3239f4df-4beb-4794-9f8e-6f770d6e7135 · outbound

This paper cites I., Baratin, A., Rajeshwar, S., Ozair, S., Bengio, Y., Courville, A., and Hjelm, D.

Adversarial Dependence Minimization I., Baratin, A., Rajeshwar, S., Ozair, S., Bengio, Y., Courville, A., and Hjelm, D

Reference 5

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Observation a4b05d89-d573-417a-85e7-8f5456ae6ce6 · outbound

This paper cites an unresolved cited work.

Adversarial Dependence Minimization Unresolved cited work

Reference 6

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Observation 509ef7b2-aa1f-4043-867c-6251dd780a27 · outbound

This paper cites Representation learning: A review and new perspectives.

Adversarial Dependence Minimization Representation learning: A review and new perspectives

Reference 7

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Observation 75f03cd1-b01c-47e9-8a35-d6450691bcd8 · outbound

This paper cites Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning.

Adversarial Dependence Minimization Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning

Reference 8

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Observation 973713d5-f76a-4c10-879d-1adaefa1a3c3 · outbound

This paper cites Learning Independent Features with Adversarial Nets for Non-linear ICA.

Adversarial Dependence Minimization Learning Independent Features with Adversarial Nets for Non-linear ICA

Reference 9

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Observation f74ae456-d6eb-4fb1-aa78-684a7a9ad9b9 · outbound

This paper cites Function classes for identifiable nonlinear independent component analysis.

Adversarial Dependence Minimization Function classes for identifiable nonlinear independent component analysis

Reference 10

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Source-reported events for the cited work

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Observation d3fcdcc4-1b2c-417d-85b5-7c8f9691fc72 · outbound

This paper cites Understanding disentangling in $\beta$-VAE.

Adversarial Dependence Minimization Understanding disentangling in $\beta$-VAE

Reference 11

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Observation 960c6fe9-1c55-4706-922b-6b989da796b4 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

Adversarial Dependence Minimization Emerging properties in self-supervised vision transformers

Reference 12

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Observation fd6c95a0-6646-4195-acb8-3d4e554b9c47 · outbound

This paper cites T., Li, X., Grosse, R.

Adversarial Dependence Minimization T., Li, X., Grosse, R

Reference 13

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Observation db091db2-3f9a-445f-9730-8833cca7b2aa · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Adversarial Dependence Minimization A simple framework for contrastive learning of visual representations

Reference 14

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Observation 9564ba36-e96f-4fa2-9baf-066a404127ee · outbound

This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets.

Adversarial Dependence Minimization Infogan: Interpretable representation learning by information maximizing generative adversarial nets

Reference 15

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Source-reported events for the cited work

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Observation 2adb564e-f2f6-4fe1-b413-2c36921e9d3b · outbound

This paper cites Support-vector networks.

Adversarial Dependence Minimization Support-vector networks

Reference 16

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Observation 44c4a6fc-5613-484b-b943-f7f48ab041f8 · outbound

This paper cites Approximation by superpositions of a sigmoidal function.

Adversarial Dependence Minimization Approximation by superpositions of a sigmoidal function

Reference 17

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Observation 625c6ca3-265c-400b-aadc-18a7e99f5fef · outbound

This paper cites Analyse des liaisons de probabilit \'e.

Adversarial Dependence Minimization Analyse des liaisons de probabilit \'e

Reference 18

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Observation 963df028-dfb8-4a86-ad9f-37f3f33cbac2 · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

Adversarial Dependence Minimization Imagenet: A large-scale hierarchical image database

Reference 19

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Observation 6d32ca7d-5e92-402f-aee9-ccca52ecdf01 · outbound

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Adversarial Dependence Minimization Unresolved cited work

Reference 20

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Observation c2ef31cd-d8fb-4c38-b8e1-fef203795a30 · outbound

This paper cites Whitening for self-supervised representation learning.

Adversarial Dependence Minimization Whitening for self-supervised representation learning

Reference 21

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Observation 07273243-46a2-4ab4-83a5-66c9c7eb863a · outbound

This paper cites Generative adversarial nets.

Adversarial Dependence Minimization Generative adversarial nets

Reference 22

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Observation a16a7346-b8eb-447b-8987-c4dcf19e2bab · outbound

This paper cites Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour.

Adversarial Dependence Minimization Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Reference 23

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This paper cites Bootstrap your own latent-a new approach to self-supervised learning.

Adversarial Dependence Minimization Bootstrap your own latent-a new approach to self-supervised learning

Reference 24

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Observation 6859ee70-3a8e-4cd6-9137-12bfa2e9d224 · outbound

This paper cites Deep residual learning for image recognition.

Adversarial Dependence Minimization Deep residual learning for image recognition

Reference 25

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Observation 5c260ec7-d8ab-4e0b-8481-0dee3385f8cd · outbound

This paper cites Momentum contrast for unsupervised visual representation learning.

Adversarial Dependence Minimization Momentum contrast for unsupervised visual representation learning

Reference 26

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Observation 834d5106-abc3-41d1-8f83-f87be10ff2ec · outbound

This paper cites Gaussian Error Linear Units (GELUs).

Adversarial Dependence Minimization Gaussian Error Linear Units (GELUs)

Reference 27

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This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Adversarial Dependence Minimization beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 28

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Adversarial Dependence Minimization Unresolved cited work

Reference 29

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Observation 9f022a87-cd24-4df4-869c-5d73c4131ded · outbound

This paper cites E., Osindero, S., and Teh, Y.-W.

Adversarial Dependence Minimization E., Osindero, S., and Teh, Y.-W

Reference 30

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Adversarial Dependence Minimization D., Fedorov, A., Lavoie-Marchildon, S., Grewal, K., Bachman, P., Trischler, A., and Bengio, Y

Reference 31

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This paper cites Multilayer feedforward networks are universal approximators.

Adversarial Dependence Minimization Multilayer feedforward networks are universal approximators

Reference 32

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This paper cites Analysis of a complex of statistical variables into principal components.

Adversarial Dependence Minimization Analysis of a complex of statistical variables into principal components

Reference 33

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Adversarial Dependence Minimization On feature decorrelation in self-supervised learning

Reference 34

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Adversarial Dependence Minimization Decorrelated batch normalization

Reference 35

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Adversarial Dependence Minimization and Morioka, H

Reference 36

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Adversarial Dependence Minimization and Oja, E

Reference 37

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Adversarial Dependence Minimization and Szegedy, C

Reference 38

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Adversarial Dependence Minimization Understanding dimensional collapse in contrastive self-supervised learning

Reference 39

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This paper cites Clevr: A diagnostic dataset for compositional language and elementary visual reasoning.

Adversarial Dependence Minimization Clevr: A diagnostic dataset for compositional language and elementary visual reasoning

Reference 40

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Adversarial Dependence Minimization and Herault, J

Reference 41

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Adversarial Dependence Minimization and Karhunen, J

Reference 42

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Adversarial Dependence Minimization Variational autoencoders and nonlinear ica: A unifying framework

Reference 43

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Adversarial Dependence Minimization and Mnih, A

Reference 44

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Adversarial Dependence Minimization Auto-Encoding Variational Bayes

Reference 45

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Adversarial Dependence Minimization Unresolved cited work

Reference 46

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Adversarial Dependence Minimization Unresolved cited work

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Adversarial Dependence Minimization and Yang, X

Reference 48

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Adversarial Dependence Minimization Y., Pinkus, A., and Schocken, S

Reference 49

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Adversarial Dependence Minimization Learning disentangled representation with pairwise independence

Reference 50

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Adversarial Dependence Minimization An application of the principle of maximum information preservation to linear systems

Reference 51

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Adversarial Dependence Minimization Challenging common assumptions in the unsupervised learning of disentangled representations

Reference 52

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Adversarial Dependence Minimization SGDR: Stochastic Gradient Descent with Warm Restarts

Reference 53

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Adversarial Dependence Minimization Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations

Reference 54

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Adversarial Dependence Minimization Unresolved cited work

Reference 55

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Adversarial Dependence Minimization Scikit-learn: Machine learning in P ython

Reference 56

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Adversarial Dependence Minimization and Torrecilla, J

Reference 57

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Observation c748fe3a-f76f-4ebc-9bee-93c28cf8664e · outbound

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Adversarial Dependence Minimization E., Hinton, G

Reference 58

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Observation 68095bd7-6b32-4819-8953-2c16cc0fda69 · outbound

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Adversarial Dependence Minimization E., Hinton, G

Reference 59

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Adversarial Dependence Minimization J., Rizzo, M

Reference 60

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Observation 80a88b8b-70c1-4c52-bcdd-f1964f594bbb · outbound

This paper cites and Jutten, C.

Adversarial Dependence Minimization and Jutten, C

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.137666Z

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Observation 95e82d14-1d17-4cbb-af1a-70fa6b19ad12 · outbound

This paper cites H., Pascanu, R., Blundell, C., and Mitrovic, J.

Adversarial Dependence Minimization H., Pascanu, R., Blundell, C., and Mitrovic, J

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:33:46.081904Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 769f92dc-8d34-4d9b-9f38-e0260f8568ab · outbound

This paper cites Large margin methods for structured and interdependent output variables.

Adversarial Dependence Minimization Large margin methods for structured and interdependent output variables

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:33:46.061912Z

Source-reported events for the cited work

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Observation 197a4055-d73a-44f2-9d61-988ec2352547 · outbound

This paper cites No representation rules them all in category discovery.

Adversarial Dependence Minimization No representation rules them all in category discovery

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:33:46.041115Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5a6c3d5c-ee5f-40fe-bb71-7a68326dd397 · outbound

This paper cites X., and Lin, D.

Adversarial Dependence Minimization X., and Lin, D

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.174359Z

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Observation b163ec8d-723b-4c4a-935b-61ec995fabd7 · outbound

This paper cites Independent principal component analysis for biologically meaningful dimension reduction of large biological data sets.

Adversarial Dependence Minimization Independent principal component analysis for biologically meaningful dimension reduction of large biological data sets

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:33:46.008427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 378c7145-9fb4-4e0e-beac-ba9f1ddd1728 · outbound

This paper cites Large Batch Training of Convolutional Networks.

Adversarial Dependence Minimization Large Batch Training of Convolutional Networks

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.201089Z

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Observation ec263cde-a1e1-4e83-bffa-390a1e0e3a66 · outbound

This paper cites Barlow twins: Self-supervised learning via redundancy reduction.

Adversarial Dependence Minimization Barlow twins: Self-supervised learning via redundancy reduction

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.210073Z

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Observation fb37cdac-16f7-41a9-b541-24d8c8613153 · outbound

This paper cites @esa (Ref.

Adversarial Dependence Minimization @esa (Ref

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.217971Z

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Observation b6afabf6-fb58-4d63-9147-8d38ed864c93 · outbound

This paper cites an unresolved cited work.

Adversarial Dependence Minimization Unresolved cited work

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.225485Z

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Observation a26c88e9-6e69-4f44-8652-2b63e2900396 · outbound

This paper cites " F 0 @P!1 234 `p.

Adversarial Dependence Minimization " F 0 @P!1 234 `p

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-09T05:33:45.232723Z

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Pith citing papers

Observation cba0488d-25e4-4c44-b01c-09d1573b69fb · inbound

Self-Supervised Learning with a Multi-Task Latent Space Objective cites this paper.

Self-Supervised Learning with a Multi-Task Latent Space Objective Adversarial Dependence Minimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T04:08:14.195239Z

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