Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:20:24.532319Z
Paper Citation Record · LEDGER
A Unified Data Representation Learning for Non-parametric Two-sample Testing
As of 19 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 2 inbound Pith citation observations for arXiv:2412.00613.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T20:54:18.986256Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T20:36:12.075431Z
Reference resolution
65 of 65 outbound references displayed
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- verified fuzzy48
- unresolved13
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 428c72ef-d844-4a1a-84db-ee96d66fb27f · outbound
This paper cites A discriminative model for semi-supervised learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing A discriminative model for semi-supervised learning
Reference 1
- Resolution
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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 2c1ebe32-ecf9-4f2c-8488-d5c6cc4f3be8 · outbound
This paper cites Model-agnostic out-of-distribution detection using combined statistical tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Model-agnostic out-of-distribution detection using combined statistical tests
Reference 2
- Resolution
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Source-reported events for the cited work
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Observation 227e1f09-91a4-4d0f-ab4e-2eb84bc95231 · outbound
This paper cites MMD - FUSE : Learning and Combining Kernels for Two - Sample Testing Without Data Splitting.
A Unified Data Representation Learning for Non-parametric Two-sample Testing MMD - FUSE : Learning and Combining Kernels for Two - Sample Testing Without Data Splitting
Reference 3
- Resolution
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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 de36ce79-1ebe-429c-a103-eba0948247c9 · outbound
This paper cites Sutherland, Michael Arbel, and Arthur Gretton.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sutherland, Michael Arbel, and Arthur Gretton
Reference 4
- Resolution
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Source-reported events for the cited work
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Observation 2e00b1f2-2949-4fa4-acc6-ad7baf61e61e · outbound
This paper cites Kernelized cumulants: Beyond kernel mean embeddings.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Kernelized cumulants: Beyond kernel mean embeddings
Reference 5
- Resolution
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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 765c729f-2875-4ae3-850e-6e5897f756d8 · outbound
This paper cites A sharp concentration inequality with application.
A Unified Data Representation Learning for Non-parametric Two-sample Testing A sharp concentration inequality with application
Reference 6
- Resolution
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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 50afb185-20aa-4de6-b68c-379c7ef32fff · outbound
This paper cites Kappa updated ensemble for drifting data stream mining.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Kappa updated ensemble for drifting data stream mining
Reference 7
- Resolution
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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 3f77a127-df0b-4f81-9dcb-3ca11ce0360d · outbound
This paper cites Semi-Supervised Learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Semi-Supervised Learning
Reference 8
- Resolution
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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 ed800c0f-7342-4d93-875c-13fe30c2892a · outbound
This paper cites Friedman.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Friedman
Reference 9
- Resolution
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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 9616e38c-2d20-45da-a17d-c460b4c4075f · outbound
This paper cites Neural tangent kernel maximum mean discrepancy, 2021.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Neural tangent kernel maximum mean discrepancy, 2021
Reference 10
- Resolution
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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 0678dc2c-0ec5-4bbd-996f-ae9c5317fc53 · outbound
This paper cites Sutherland.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sutherland
Reference 11
- Resolution
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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 fe7abc68-89e8-428b-8641-597f632f6049 · outbound
This paper cites Imagenet: A large-scale hierarchical image database.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Imagenet: A large-scale hierarchical image database
Reference 12
- Resolution
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Source-reported events for the cited work
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Observation 796f46c8-fd3b-4e3e-ac27-c63a7462c8b3 · outbound
This paper cites Binomial approximation to the Poisson binomial distribution.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Binomial approximation to the Poisson binomial distribution
Reference 13
- Resolution
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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 72523e2f-30a0-448e-98af-180283b53e64 · outbound
This paper cites Learning bounds for open-set learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Learning bounds for open-set learning
Reference 14
- Resolution
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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 98bf2587-3d39-4b21-a81d-1d1903aaf0a7 · outbound
This paper cites Open set domain adaptation: Theoretical bound and algorithm.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Open set domain adaptation: Theoretical bound and algorithm
Reference 15
- Resolution
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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 a1bbbeba-d693-4d24-91dc-0b44fc3682ff · outbound
This paper cites Robust hypothesis testing using W asserstein uncertainty sets.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Robust hypothesis testing using W asserstein uncertainty sets
Reference 16
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0e850470-6c41-4130-a641-2bc3a1e1fe5d · outbound
This paper cites Maximum mean discrepancy test is aware of adversarial attacks.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Maximum mean discrepancy test is aware of adversarial attacks
Reference 17
- Resolution
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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 6a37503b-b4de-4304-a91f-b8503b0c10a0 · outbound
This paper cites Practical methods for graph two-sample testing.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Practical methods for graph two-sample testing
Reference 18
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 42de1bf4-10db-4c5f-9b8f-2ab9f82eb080 · outbound
This paper cites Two-sample tests for large random graphs using network statistics.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Two-sample tests for large random graphs using network statistics
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation f2b83e47-ba55-40c7-8bef-85a9937764da · outbound
This paper cites Domain adaptation with conditional transferable components.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Domain adaptation with conditional transferable components
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 76357558-2fd5-436d-aed5-6d3fa7459e9e · outbound
This paper cites Rasch, Bernhard Sch \" o lkopf, and Alexander J.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Rasch, Bernhard Sch \" o lkopf, and Alexander J
Reference 21
- Resolution
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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 cd0e6e97-54a3-460e-b8cc-e62d7ba3f92c · outbound
This paper cites Optimal kernel choice for large-scale two-sample tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Optimal kernel choice for large-scale two-sample tests
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1974add9-dab9-4560-ae2c-3ee319ca0433 · outbound
This paper cites Multivariate tests of association based on univariate tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Multivariate tests of association based on univariate tests
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation ae3c7957-6462-4d14-a0ee-b1accff661c0 · outbound
This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.
A Unified Data Representation Learning for Non-parametric Two-sample Testing beta-vae: Learning basic visual concepts with a constrained variational framework
Reference 24
- Resolution
- verified fuzzy
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Source-reported events for the cited work
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Observation ab24e12c-7e14-47a8-8997-671cb02f4718 · outbound
This paper cites Interpretable distribution features with maximum testing power.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Interpretable distribution features with maximum testing power
Reference 25
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 354713d2-d300-43d1-9db2-3c85b3ce8287 · outbound
This paper cites Auto-Encoding Variational Bayes.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Auto-Encoding Variational Bayes
Reference 26
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2f69893-8ed7-4d48-a6e0-a3746283204d · outbound
This paper cites Semi-supervised learning with deep generative models.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Semi-supervised learning with deep generative models
Reference 27
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 1d169fd6-432c-4366-86fb-e88bd11bbd95 · outbound
This paper cites Two-sample testing using deep learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Two-sample testing using deep learning
Reference 28
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 8170b09b-6fc3-445d-aca1-6861af44ba9c · outbound
This paper cites Kolmogorov.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Kolmogorov
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 47c41b6c-61ec-4ae3-941e-65969e7e4c78 · outbound
This paper cites u bler, Wittawat Jitkrittum, Bernhard Sch\.
A Unified Data Representation Learning for Non-parametric Two-sample Testing u bler, Wittawat Jitkrittum, Bernhard Sch\
Reference 30
- Resolution
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Observation 84ccede3-a161-48ef-8dcd-fa34ee06ba2c · outbound
This paper cites u bler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, and Bernhard Sch \.
A Unified Data Representation Learning for Non-parametric Two-sample Testing u bler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, and Bernhard Sch \
Reference 31
- Resolution
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Observation 203c9eee-6abd-48c3-9656-57634785dee5 · outbound
This paper cites Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, and Krikamol Muandet.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, and Krikamol Muandet
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 0704db1d-18db-4383-b80c-4330bd7babf9 · outbound
This paper cites Gradient-based learning applied to document recognition.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Gradient-based learning applied to document recognition
Reference 33
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation a78ae7af-05b2-44ff-a20d-6437428ef3a1 · outbound
This paper cites Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks
Reference 34
- Resolution
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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 0e0d1ced-1c52-4427-8bed-6f74b6146175 · outbound
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A Unified Data Representation Learning for Non-parametric Two-sample Testing Unresolved cited work
Reference 35
- Resolution
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Source-reported events for the cited work
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Observation 73b0df97-a398-40b3-9e5f-26f091c61669 · outbound
This paper cites MONK outlier-robust mean embedding estimation by median-of-means.
A Unified Data Representation Learning for Non-parametric Two-sample Testing MONK outlier-robust mean embedding estimation by median-of-means
Reference 36
- Resolution
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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 3a51db80-0fc0-4b51-846e-8baa30a9f689 · outbound
This paper cites Sutherland.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sutherland
Reference 37
- Resolution
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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 58d0511a-a6fa-4e58-b47e-f44bb19ce458 · outbound
This paper cites Sutherland.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sutherland
Reference 38
- Resolution
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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 16725924-108f-4629-b35c-6f1fe08e0162 · outbound
This paper cites Revisiting Classifier Two-Sample Tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Revisiting Classifier Two-Sample Tests
Reference 39
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f60e385a-ff6f-4606-abb6-533744305f6f · outbound
This paper cites Revisiting classifier two-sample tests, 2018 b.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Revisiting classifier two-sample tests, 2018 b
Reference 40
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation b193896e-aaf0-4c09-8027-3472486facc5 · outbound
This paper cites Exploiting MMD and S inkhorn divergences for fair and transferable representation learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Exploiting MMD and S inkhorn divergences for fair and transferable representation learning
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.404471Z
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 566cae2f-e8c8-434d-aed4-fa342b75f7dd · outbound
This paper cites E-Valuating Classifier Two-Sample Tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing E-Valuating Classifier Two-Sample Tests
Reference 42
- Resolution
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Source-reported events for the cited work
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Observation 0d3df890-e186-4e7e-a496-5ce0710bd86e · outbound
This paper cites Unsupervised representation learning with deep convolutional generative adversarial networks.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Unsupervised representation learning with deep convolutional generative adversarial networks
Reference 43
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fdc598f1-968c-48c1-9897-ee03404ea6a3 · outbound
This paper cites On W asserstein two-sample testing and related families of nonparametric tests.
A Unified Data Representation Learning for Non-parametric Two-sample Testing On W asserstein two-sample testing and related families of nonparametric tests
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.379660Z
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 e0b70265-0404-4bb4-8355-33f44fdfbbd4 · outbound
This paper cites Stylegan-xl: Scaling stylegan to large diverse datasets.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Stylegan-xl: Scaling stylegan to large diverse datasets
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.364348Z
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 e3cab6ef-6121-452d-984f-e0e62b95ca48 · outbound
This paper cites MMD Aggregated Two - Sample Test.
A Unified Data Representation Learning for Non-parametric Two-sample Testing MMD Aggregated Two - Sample Test
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.349552Z
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 443f648b-da17-48b4-adc1-c5d62f685e04 · outbound
This paper cites Approximation theorems of mathematical statistics.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Approximation theorems of mathematical statistics
Reference 47
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 661d5e60-ff4a-4c51-93d8-a6737b997a15 · outbound
This paper cites an unresolved cited work.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Unresolved cited work
Reference 48
- Resolution
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- raw_fallback, observed 2026-08-12T05:20:25.327825Z
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 09417c2c-1b14-4bbf-b506-01d957152fd4 · outbound
This paper cites Fixmatch: Simplifying semi-supervised learning with consistency and confidence.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Fixmatch: Simplifying semi-supervised learning with consistency and confidence
Reference 49
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 811c14e3-c9d6-4fe8-a0ca-eba250927662 · outbound
This paper cites A segment-based drift adaptation method for data streams.
A Unified Data Representation Learning for Non-parametric Two-sample Testing A segment-based drift adaptation method for data streams
Reference 50
- Resolution
- verified exact
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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 8a2141ef-cd35-48cb-983c-3eebc51551b5 · outbound
This paper cites Graph-based semi-supervised learning: A comprehensive review, 2021 b.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Graph-based semi-supervised learning: A comprehensive review, 2021 b
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.304601Z
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 6ed38f71-fc75-418f-b8a9-b7c69381e0fd · outbound
This paper cites Carbonell, and Kun Zhang.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Carbonell, and Kun Zhang
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.286770Z
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 ddb61e20-a882-408b-b8ef-37014f507c55 · outbound
This paper cites Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, and Arthur Gretton.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alex Smola, and Arthur Gretton
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.270338Z
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 e1c7e783-c40c-4d60-96b1-3ee157f9e8e8 · outbound
This paper cites Sz \' e kely and Maria L.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Sz \' e kely and Maria L
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.256656Z
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 cef0a2fa-7704-4288-9254-920a9bad1e0d · outbound
This paper cites Driftsurf: Stable-state/reactive-state learning under concept drift.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Driftsurf: Stable-state/reactive-state learning under concept drift
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.243950Z
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 66e15de6-4685-4010-b36d-f44ec53ee2a9 · outbound
This paper cites Blanchet, Daniel Kuhn, and Viet Anh Nguyen.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Blanchet, Daniel Kuhn, and Viet Anh Nguyen
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.230324Z
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 32fb77be-f057-48fa-9324-0eadde16baf6 · outbound
This paper cites Recent Advances in Autoencoder-Based Representation Learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Recent Advances in Autoencoder-Based Representation Learning
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:24.495039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4c77682-df41-4329-9477-64217a706ac2 · outbound
This paper cites Recent Advances in Autoencoder - Based Representation Learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Recent Advances in Autoencoder - Based Representation Learning
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.216316Z
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 85df5e78-989a-44c7-bb25-266330d149c1 · outbound
This paper cites Unsupervised data augmentation for consistency training.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Unsupervised data augmentation for consistency training
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:24.504689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d79079f-c818-42a1-9496-fb0febaa7208 · outbound
This paper cites A survey on deep semi-supervised learning.
A Unified Data Representation Learning for Non-parametric Two-sample Testing A survey on deep semi-supervised learning
Reference 60
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-12T05:20:24.910660Z
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 b3155986-cef9-43ba-9026-c3108ab67b9e · outbound
This paper cites How does the combined risk affect the performance of unsupervised domain adaptation approaches? In AAAI, 2021.
A Unified Data Representation Learning for Non-parametric Two-sample Testing How does the combined risk affect the performance of unsupervised domain adaptation approaches? In AAAI, 2021
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T05:20:25.194486Z
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 c153ae56-e5a1-4e6a-b632-872b26f4585a · outbound
This paper cites write newline.
A Unified Data Representation Learning for Non-parametric Two-sample Testing write newline
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:24.518397Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14389b7f-0ed9-4b1b-b951-7bca5d492693 · outbound
This paper cites @esa (Ref.
A Unified Data Representation Learning for Non-parametric Two-sample Testing @esa (Ref
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:24.523471Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bd72cd42-0556-4f9c-aa77-1c33cc8606cc · outbound
This paper cites an unresolved cited work.
A Unified Data Representation Learning for Non-parametric Two-sample Testing Unresolved cited work
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T05:20:24.527950Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6daa48b-4c88-403c-8f1c-32ed9ca05881 · outbound
This paper cites rg] ( sx&ziC0 6=E! !hP3 R * t z Iym p 4+@D N6: S3£yON gG [4 F.
A Unified Data Representation Learning for Non-parametric Two-sample Testing rg] ( sx&ziC0 6=E! !hP3 R * t z Iym p 4+@D N6: S3£yON gG [4 F
Reference 65
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-12T05:20:24.725031Z
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
Observation 7d67f7a1-b99e-46cc-9dd5-50e3c43d0692 · inbound
A Semi-Supervised Kernel Two-Sample Test cites this paper.
A Semi-Supervised Kernel Two-Sample Test A Unified Data Representation Learning for Non-parametric Two-sample Testing
Reference 177
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T16:26:05.701202Z
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 911514b6-f1d8-4c48-af0c-f13e69d28223 · inbound
Counterfactual Explanations for Deep Two-Sample Testing cites this paper.
Counterfactual Explanations for Deep Two-Sample Testing A Unified Data Representation Learning for Non-parametric Two-sample Testing
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T20:36:12.077191Z
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.