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Paper Citation Record · LEDGER

Variational Learning of Disentangled Representations

As of 21 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2506.17182.

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

pith.paper-citation-record.v1
2506.17182 v3

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:18:28.242348Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+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

75 of 75 outbound references displayed

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  • verified fuzzy48
  • unresolved27
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06f4ab42-1505-4271-a02a-0f3f0e6b99c5 · outbound

This paper cites Brain lesion detection using a robust variational autoencoder and transfer learning.

Variational Learning of Disentangled Representations Brain lesion detection using a robust variational autoencoder and transfer learning

Reference 1

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Observation c1c894c8-4851-4b87-89ce-d396460dd2c8 · outbound

This paper cites Adversarial invariant feature learning with accuracy constraint for domain generalization.

Variational Learning of Disentangled Representations Adversarial invariant feature learning with accuracy constraint for domain generalization

Reference 2

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Observation d67b75e2-c379-4b4b-b522-c4bb896d370f · outbound

This paper cites Invariant Risk Minimization.

Variational Learning of Disentangled Representations Invariant Risk Minimization

Reference 3

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Observation d29239e9-1480-4507-a075-5c069abd400d · outbound

This paper cites Patches: A representation learning framework for decoding shared and condition-specific transcriptional programs in wound healing.

Variational Learning of Disentangled Representations Patches: A representation learning framework for decoding shared and condition-specific transcriptional programs in wound healing

Reference 4

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Observation 24abd6ee-4826-4b65-a26e-627b43aedf4b · outbound

This paper cites Mutual information neural estimation.

Variational Learning of Disentangled Representations Mutual information neural estimation

Reference 5

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Source-reported events for the cited work

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Observation 388ab23a-73b0-44b1-8e07-e265fb4b7ed5 · outbound

This paper cites Robust solutions of optimization problems affected by uncertain probabilities.

Variational Learning of Disentangled Representations Robust solutions of optimization problems affected by uncertain probabilities

Reference 6

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Observation c53e592b-b8bf-4fdc-905f-324e7679567f · outbound

This paper cites Deep generative modeling of sample-level heterogeneity in single-cell genomics.

Variational Learning of Disentangled Representations Deep generative modeling of sample-level heterogeneity in single-cell genomics

Reference 7

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Source-reported events for the cited work

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Observation 104a620e-4e6a-4fc3-91d4-d61b267bcb82 · outbound

This paper cites Hallucinating agnostic images to generalize across domains.

Variational Learning of Disentangled Representations Hallucinating agnostic images to generalize across domains

Reference 8

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Observation 6470b661-3e05-47e9-b4f5-a4b96cae1e04 · outbound

This paper cites Domain adversarial active learning for domain generalization classification.

Variational Learning of Disentangled Representations Domain adversarial active learning for domain generalization classification

Reference 9

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Observation b535817d-f7d2-4899-b0c8-0043352d6c8d · outbound

This paper cites Adversarial bayesian augmentation for single-source domain generalization.

Variational Learning of Disentangled Representations Adversarial bayesian augmentation for single-source domain generalization

Reference 10

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Observation 6cdbb4aa-fe2e-40b4-ad0c-e97e72dfc59d · outbound

This paper cites Madg: margin-based adversarial learning for domain generalization.

Variational Learning of Disentangled Representations Madg: margin-based adversarial learning for domain generalization

Reference 11

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Observation c8c348cf-1e3d-44d8-8d23-e3d115350a31 · outbound

This paper cites The mnist database of handwritten digit images for machine learning research.

Variational Learning of Disentangled Representations The mnist database of handwritten digit images for machine learning research

Reference 12

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Observation fa6448c0-f10c-41ab-a794-6ae0a50f9b7d · outbound

This paper cites Deep domain generalization with structured low-rank constraint.

Variational Learning of Disentangled Representations Deep domain generalization with structured low-rank constraint

Reference 13

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Source-reported events for the cited work

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Observation 3b93d9b3-5ac0-454a-b796-29a42c873f92 · outbound

This paper cites Learning models with uniform performance via distributionally robust optimization.

Variational Learning of Disentangled Representations Learning models with uniform performance via distributionally robust optimization

Reference 14

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Observation ed440f64-aa5c-4463-9a90-5519e95c50dd · outbound

This paper cites Statistics of robust optimization: A generalized empirical likelihood approach.

Variational Learning of Disentangled Representations Statistics of robust optimization: A generalized empirical likelihood approach

Reference 15

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Observation 290a1d82-8a37-4d8b-b948-b0e550712f5e · outbound

This paper cites Two modeling strategies for empirical bayes estimation.

Variational Learning of Disentangled Representations Two modeling strategies for empirical bayes estimation

Reference 16

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Observation 005c3f9d-5a7b-41a2-8c1f-4a0c400c053b · outbound

This paper cites One-shot learning of object categories.

Variational Learning of Disentangled Representations One-shot learning of object categories

Reference 17

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Source-reported events for the cited work

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Observation 2251c9c6-a3de-4c5a-95a9-638c94a0414b · outbound

This paper cites Posterior regularization for structured latent variable models.

Variational Learning of Disentangled Representations Posterior regularization for structured latent variable models

Reference 18

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Observation ec7afab1-8be0-4ff0-9726-440c3a234c04 · outbound

This paper cites Domain generalization for object recognition with multi-task autoencoders.

Variational Learning of Disentangled Representations Domain generalization for object recognition with multi-task autoencoders

Reference 19

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Observation c7b23df5-c7c5-423d-8537-54966755de0a · outbound

This paper cites Design of potent antimalarials with generative chemistry.

Variational Learning of Disentangled Representations Design of potent antimalarials with generative chemistry

Reference 20

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Observation 9d8d745c-9f9f-4689-af6d-45a95ec74e5b · outbound

This paper cites Improving diversity with adversarially learned transformations for domain generalization.

Variational Learning of Disentangled Representations Improving diversity with adversarially learned transformations for domain generalization

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 6d48caf9-c028-4b21-b6c0-31f20e2b89de · outbound

This paper cites Generative adversarial networks.

Variational Learning of Disentangled Representations Generative adversarial networks

Reference 22

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Observation 654e0752-ef0e-4874-ad7c-732ea5ac5100 · outbound

This paper cites Dimensionality reduction by learning an invariant mapping.

Variational Learning of Disentangled Representations Dimensionality reduction by learning an invariant mapping

Reference 23

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Observation c8b70a3c-9feb-4c37-8a48-3e8d02c2dab2 · outbound

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

Variational Learning of Disentangled Representations beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 24

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Observation 393205b5-d8ae-455a-9624-4ae47b70d8d1 · outbound

This paper cites Denoising diffusion probabilistic models.

Variational Learning of Disentangled Representations Denoising diffusion probabilistic models

Reference 25

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Observation 4689d3a9-6844-48a8-a372-0d73afaaa8c8 · outbound

This paper cites Deep metric learning using triplet network.

Variational Learning of Disentangled Representations Deep metric learning using triplet network

Reference 26

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Source-reported events for the cited work

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Observation 4ff93846-8053-4df5-8466-9e5a70f0faf6 · outbound

This paper cites Simple data balancing achieves competitive worst-group-accuracy.

Variational Learning of Disentangled Representations Simple data balancing achieves competitive worst-group-accuracy

Reference 27

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Observation 0bd6a2d3-4b46-4caa-ba9a-932f8d374427 · outbound

This paper cites Diva: Domain invariant variational autoencoders.

Variational Learning of Disentangled Representations Diva: Domain invariant variational autoencoders

Reference 28

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Source-reported events for the cited work

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Observation b5a8db45-6dcb-4694-b035-eeb3de2a2a4b · outbound

This paper cites Capturing Label Characteristics in VAEs.

Variational Learning of Disentangled Representations Capturing Label Characteristics in VAEs

Reference 29

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Observation bebc74f6-739c-4b21-b3bd-0d4c70db65aa · outbound

This paper cites Selfreg: Self-supervised contrastive regularization for domain generalization.

Variational Learning of Disentangled Representations Selfreg: Self-supervised contrastive regularization for domain generalization

Reference 30

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Observation c9913ffd-05a9-4eb7-b875-09eb89222852 · outbound

This paper cites Auto-encoding variational bayes.

Variational Learning of Disentangled Representations Auto-encoding variational bayes

Reference 31

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Source-reported events for the cited work

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Observation 08bc56b3-0b07-4c6c-b32a-f6485e54334e · outbound

This paper cites Learning latent subspaces in variational autoencoders.

Variational Learning of Disentangled Representations Learning latent subspaces in variational autoencoders

Reference 32

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 48d6e2c2-61e1-4f6d-a013-5cc2e561b277 · outbound

This paper cites Siamese neural networks for one-shot image recognition.

Variational Learning of Disentangled Representations Siamese neural networks for one-shot image recognition

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 3701aaca-9776-427c-bd30-f2153a48b86d · outbound

This paper cites Out-of-distribution generalization via risk extrapolation (rex).

Variational Learning of Disentangled Representations Out-of-distribution generalization via risk extrapolation (rex)

Reference 34

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Source-reported events for the cited work

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Observation f4da4a5b-5bbd-4f48-94ce-49fc3e671d56 · outbound

This paper cites Zero-data learning of new tasks.

Variational Learning of Disentangled Representations Zero-data learning of new tasks

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 2b1d26a8-ce14-4f96-805e-d3cb2c7f37ad · outbound

This paper cites Autoencoding beyond pixels using a learned similarity metric.

Variational Learning of Disentangled Representations Autoencoding beyond pixels using a learned similarity metric

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation aae7a176-b337-4092-bb65-eca2c10690df · outbound

This paper cites Domain generalization via conditional invariant representations.

Variational Learning of Disentangled Representations Domain generalization via conditional invariant representations

Reference 37

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Observation 4f39991e-07c4-4741-873d-b46d48268580 · outbound

This paper cites Efficient multi-domain learning by covariance normalization.

Variational Learning of Disentangled Representations Efficient multi-domain learning by covariance normalization

Reference 38

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Observation fa9cfec0-2f1d-4939-b2f5-b9c09b7a0b5b · outbound

This paper cites Just train twice: Improving group robustness without training group information.

Variational Learning of Disentangled Representations Just train twice: Improving group robustness without training group information

Reference 39

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Observation 6d48fdbe-e609-484e-908d-b800e0a53646 · outbound

This paper cites Deep learning face attributes in the wild.

Variational Learning of Disentangled Representations Deep learning face attributes in the wild

Reference 40

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Observation 8afd4f2c-3a28-4816-b060-c26513c778e1 · outbound

This paper cites Deep generative modeling for single-cell transcriptomics.

Variational Learning of Disentangled Representations Deep generative modeling for single-cell transcriptomics

Reference 41

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source=arxiv_source observed=2026-08-15T19:18:27.378969Z digest=sha256:42f0c75ce1ad493e2f2eb3bdd83adceb85ea5c35c935fc82272cec6779c1cd0f

Observation 9c6930fa-eb9a-43c4-869a-c6633d081138 · outbound

This paper cites Decoupled weight decay regularization.

Variational Learning of Disentangled Representations Decoupled weight decay regularization

Reference 42

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source=arxiv_source observed=2026-08-15T19:18:27.382969Z digest=sha256:8e799297700698063922699e76cdd5d67f9a719e10ea00d9860c47d2c7378041

Observation cfe675de-f8de-464a-9519-83934c279eab · outbound

This paper cites scgen predicts single-cell perturbation responses.

Variational Learning of Disentangled Representations scgen predicts single-cell perturbation responses

Reference 43

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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 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.386098Z digest=sha256:d6ff862142796d3576060ab66018b232eb2df7c651d3d7b5e321c778037ccc38

Observation febced5e-4bfd-412c-b3c7-3adb674b8f72 · outbound

This paper cites Should we embed in chemistry? a comparison of unsupervised transfer learning with pca, umap, and vae on molecular fingerprints.

Variational Learning of Disentangled Representations Should we embed in chemistry? a comparison of unsupervised transfer learning with pca, umap, and vae on molecular fingerprints

Reference 44

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.389691Z digest=sha256:f01ce4781dba9dfc4074f50b4ddf8be21b5f86191fc6410ab19760197e5f116f

Observation aa969431-ea9e-40cc-9c90-32ac4a850d28 · outbound

This paper cites Best sources forward: domain generalization through source-specific nets.

Variational Learning of Disentangled Representations Best sources forward: domain generalization through source-specific nets

Reference 45

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.402416Z digest=sha256:e5fad364f26b4a25ce508224d2903b634ef253dd9ffd2a59e2c517f26eb7e54f

Observation b59c29a5-f526-40d1-9035-9e7fd0f0c89d · outbound

This paper cites Machine Learning: An Algorithmic Perspective, Second Edition.

Variational Learning of Disentangled Representations Machine Learning: An Algorithmic Perspective, Second Edition

Reference 46

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.458122Z digest=sha256:bd9264665b272034e5685ed0524cd6a183943a49ebe1f015fef60ec344b8716f

Observation e5c23629-d643-4de3-b98c-b09fd9684e75 · outbound

This paper cites Unified deep supervised domain adaptation and generalization.

Variational Learning of Disentangled Representations Unified deep supervised domain adaptation and generalization

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:29.288010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.579576Z digest=sha256:4c0a077013c11447b938efad85df21b25c18faea1f6659b40a6908d0f66c7b2a

Observation 938d9ade-3dcd-4d42-b140-01a007d25540 · outbound

This paper cites Domain generalization via invariant feature representation.

Variational Learning of Disentangled Representations Domain generalization via invariant feature representation

Reference 48

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.610313Z digest=sha256:af9d38ff4d07699e252533c6f0b829c106d67ae525bf1022d3369e4ea92f255e

Observation 83d9c3cf-b4c4-4963-89b6-960719543f26 · outbound

This paper cites Domain generalization via ensemble stacking for face presentation attack detection.

Variational Learning of Disentangled Representations Domain generalization via ensemble stacking for face presentation attack detection

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:29.261083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.615505Z digest=sha256:e165fab3c9de73b8e9f415f13163a91f5b27ee1a27766a272ad9b06df0e24fc0

Observation 88fff36d-cabd-42fe-a7df-12c091f846e3 · outbound

This paper cites Deep metric learning via lifted structured feature embedding.

Variational Learning of Disentangled Representations Deep metric learning via lifted structured feature embedding

Reference 50

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unresolved
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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T19:18:27.619024Z digest=sha256:603320dad4cb5f3fb060958572d07191285efb7a82cbec3b9e95eeaf5e10f95e

Observation 55f77250-2a39-4dfe-a8db-afff8e248d30 · outbound

This paper cites Model-agnostic multi-domain learning with domain-specific adapters for action recognition.

Variational Learning of Disentangled Representations Model-agnostic multi-domain learning with domain-specific adapters for action recognition

Reference 51

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verified fuzzy
raw_fallback, observed 2026-08-15T19:18:29.221253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.622555Z digest=sha256:1624baf5b9cfc20967e77b4cedc0f4844aad1e9c38348c73ad5ed1ecb68be5ca

Observation f32b3051-c484-468b-9a9d-daed2016f200 · outbound

This paper cites A survey on transfer learning.

Variational Learning of Disentangled Representations A survey on transfer learning

Reference 52

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.626164Z digest=sha256:e671d25212fd7117658960edc6edf65b009d14f495ac48cae2cbee9d5e369e8f

Observation 08dfb66f-a972-466e-9504-493e91e405b3 · outbound

This paper cites Pedregosa, G.

Variational Learning of Disentangled Representations Pedregosa, G

Reference 53

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source=arxiv_source observed=2026-08-15T19:18:27.630148Z digest=sha256:d080250567c14c2586f233c3db859fb98112902757840c5a05bef5a421a123f2

Observation 8511eb83-c837-457c-9b6d-c407e06fae45 · outbound

This paper cites Causal inference by using invariant prediction: identification and confidence intervals.

Variational Learning of Disentangled Representations Causal inference by using invariant prediction: identification and confidence intervals

Reference 54

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no resolver link, observed 2026-08-15T19:18:27.632904Z

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source=arxiv_source observed=2026-08-15T19:18:27.632904Z digest=sha256:2b88b97bce3cbf924bf3b9cc5facd7cacd988b40e8bef4a35da95f3353668da3

Observation eb7d6675-7a0b-4911-a997-befa9bb607b0 · outbound

This paper cites Elements of causal inference: foundations and learning algorithms.

Variational Learning of Disentangled Representations Elements of causal inference: foundations and learning algorithms

Reference 55

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unresolved
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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:18:27.636388Z digest=sha256:d099417077d241379ee5f63afd8db59058da2c993a569d1acb717052e8559c5b

Observation 5217a56e-0dd9-4367-8469-a690b0b02160 · outbound

This paper cites Focus on the common good: Group distributional robustness follows.

Variational Learning of Disentangled Representations Focus on the common good: Group distributional robustness follows

Reference 56

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no resolver link, observed 2026-08-15T19:18:27.639720Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:18:27.639720Z digest=sha256:74f616077bbc7b50c0327211fe32d12d5d5070977454c71d09c8be8add876647

Observation 089604dd-4560-402e-9985-a538b064d75f · outbound

This paper cites Learning multiple visual domains with residual adapters.

Variational Learning of Disentangled Representations Learning multiple visual domains with residual adapters

Reference 57

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unresolved
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source=arxiv_source observed=2026-08-15T19:18:27.643737Z digest=sha256:dc13da3d66abd2f95c0791e53b32ab1795f8410b0f790443252f5db7e2bb1ea7

Observation 8dd8455a-f532-46f7-9511-f4eb492fa366 · outbound

This paper cites Efficient parametrization of multi-domain deep neural networks.

Variational Learning of Disentangled Representations Efficient parametrization of multi-domain deep neural networks

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:29.099247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.646906Z digest=sha256:c7bed6056eac0a5e29a3d4d8f74b2c95a259eaadb070fc42a907008514327b21

Observation 451f9feb-75ff-421e-aade-1dfa2ba0a480 · outbound

This paper cites An empirical bayes approach to statistics.

Variational Learning of Disentangled Representations An empirical bayes approach to statistics

Reference 59

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.650050Z digest=sha256:2f38e1c17ab5739495c0a902579a810773f7ef91ded390a4c287851ba9de25c0

Observation e726d060-ed1f-47a6-ad69-b913cd4f6068 · outbound

This paper cites Distributionally robust neural networks.

Variational Learning of Disentangled Representations Distributionally robust neural networks

Reference 60

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T19:18:27.688466Z digest=sha256:b7dc5bab678bed8a7068754c77a8e5eae09886c2bf6e21bbd9884c8fa56cdc04

Observation 591753cf-056c-408d-87d5-8b900757400e · outbound

This paper cites Class distribution shifts in zero-shot learning: Learning robust representations.

Variational Learning of Disentangled Representations Class distribution shifts in zero-shot learning: Learning robust representations

Reference 61

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:27.781480Z digest=sha256:f812fcf8118113d66ae43a4d90e3ab47029054bb4779407980c6ae155f41df07

Observation f452f3ca-a357-4da8-84a2-96b50239ad08 · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Variational Learning of Disentangled Representations Deep unsupervised learning using nonequilibrium thermodynamics

Reference 62

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source=arxiv_source observed=2026-08-15T19:18:27.865852Z digest=sha256:615312688de98f67492627571f519894ca70dd85791dfa16f133ed08173f35bd

Observation 9d4ca2d8-ceea-4bce-9840-74ece8af8d89 · outbound

This paper cites Improved deep metric learning with multi-class n-pair loss objective.

Variational Learning of Disentangled Representations Improved deep metric learning with multi-class n-pair loss objective

Reference 63

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:18:27.979403Z digest=sha256:7053cee93a32027bff02a68081fada3d797c1a4f12ce7d5096fcdc2e90b65297

Observation 16b0eb71-fab7-45d2-a38c-8f294a7f005d · outbound

This paper cites Learning structured output representation using deep conditional generative models.

Variational Learning of Disentangled Representations Learning structured output representation using deep conditional generative models

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T19:18:28.030692Z digest=sha256:99bd03a025f922dfb4bdcbfcc3652891cac813a5dc223e15eb171f72197bf3a1

Observation c486884a-8154-4fa2-9cb4-6d0394d521a1 · outbound

This paper cites Deep coral: Correlation alignment for deep domain adaptation.

Variational Learning of Disentangled Representations Deep coral: Correlation alignment for deep domain adaptation

Reference 65

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.034029Z digest=sha256:c08a7aa24ed057b007d52f00c1c8128ed4c48a015ce52f133ece130b2e1cd167

Observation 4d31d17e-3e59-4a24-ab66-0c28e5fd064d · outbound

This paper cites On calibration and out-of-domain generalization.

Variational Learning of Disentangled Representations On calibration and out-of-domain generalization

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.900069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.037638Z digest=sha256:ba7ae9a509bf83e612eefbf67cf620573940d62d1cbba3fb98e3ce1435ec5eee

Observation 8199674c-38e3-43b6-8cbc-f77079327908 · outbound

This paper cites Select-additive learning: Improving generalization in multimodal sentiment analysis.

Variational Learning of Disentangled Representations Select-additive learning: Improving generalization in multimodal sentiment analysis

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.866840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.041049Z digest=sha256:68ded1d492423ca82c7ca264a0c3469bb7903f643c52c38ebad1d1575d67fe00

Observation 97827b8a-ca25-4819-847a-adeed1af8c68 · outbound

This paper cites Learning robust representations by projecting superficial statistics out.

Variational Learning of Disentangled Representations Learning robust representations by projecting superficial statistics out

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.767537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.044094Z digest=sha256:ec7338140d1f8417311b033fe5d1f98a775cc89d3adedf1afe64b2a5802b3b0b

Observation e06236bc-0b68-47eb-9d7d-b1cd9e470158 · outbound

This paper cites Distributionally robust post-hoc classifiers under prior shifts.

Variational Learning of Disentangled Representations Distributionally robust post-hoc classifiers under prior shifts

Reference 69

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verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.755909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.048394Z digest=sha256:a8951660030b7145815e74eb97de4cca26a83254355fbdc91f7af35dc319bebb

Observation 090eb0bc-28bb-46bf-940a-36354ee80a1d · outbound

This paper cites Sampling matters in deep embedding learning.

Variational Learning of Disentangled Representations Sampling matters in deep embedding learning

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.744659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.051755Z digest=sha256:07011d587db6178e8c0f2b6b2ac030b1589d205ddf8d2ab656af6f1b2e89c762

Observation da53a17f-f80b-4f4b-a795-09b70fa595a3 · outbound

This paper cites Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models.

Variational Learning of Disentangled Representations Probabilistic harmonization and annotation of single-cell transcriptomics data with deep generative models

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.730447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.055095Z digest=sha256:4a3873f3599dcecfa2ec2301b0345f21473b129cebc053292224f7d10d8b0660

Observation 4c24a6a4-c9b4-45f0-b0ee-4888180222f0 · outbound

This paper cites Signal-to-noise ratio: A robust distance metric for deep metric learning.

Variational Learning of Disentangled Representations Signal-to-noise ratio: A robust distance metric for deep metric learning

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.680557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.059562Z digest=sha256:3f08af33b0ab501dda3d8e7d7ed7d334017ead036c17ac43769559f5241f3ee9

Observation 705e7a53-8bcb-4a9b-a9ab-3f16a0a72731 · outbound

This paper cites A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition.

Variational Learning of Disentangled Representations A variational local weighted deep sub-domain adaptation network for remaining useful life prediction facing cross-domain condition

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.521434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.181144Z digest=sha256:1a909ebc8e5e061aee6d677a2482ddde174e66d12aed23891aebb45fd07b5b77

Observation 953a6f99-bd85-4d15-8235-f7321b244754 · outbound

This paper cites Domain adaptive ensemble learning.

Variational Learning of Disentangled Representations Domain adaptive ensemble learning

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.509531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.239500Z digest=sha256:22eb8c8c155ef80fbc7d5c777583e06289abddc7518f1f447c723f8040320e69

Observation f337a660-3dbc-4af5-9352-9a179066c5f1 · outbound

This paper cites Localized adversarial domain generalization.

Variational Learning of Disentangled Representations Localized adversarial domain generalization

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T19:18:28.400617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-08-15T19:18:28.242348Z digest=sha256:102bd5951820707c90446b992dcdfeae752c6cd0127f173e1eaeb4d4854ac277

Pith citing papers

No inbound Pith citation observations are available.