Paper Citation Record · LEDGER

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation

As of 7 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:1906.09693.

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

pith.paper-citation-record.v1
1906.09693 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T17:47:24.595944Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

25 of 25 outbound references displayed

verified exact0
verified fuzzy25
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 328b3838-5ce6-45ea-801d-42ee3fa584f2 · outbound

This paper cites A theory of learning from different domains.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation A theory of learning from different domains

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.896635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 5fea05b0-aec2-4de8-8030-aca43d2e5fa9 · outbound

This paper cites Weight uncertainty in neural network.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Weight uncertainty in neural network

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.855347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6c115f0a-1998-4611-9b91-7e963d0c9a0d · outbound

This paper cites Re-weighted adversarial adaptation network for unsupervised domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Re-weighted adversarial adaptation network for unsupervised domain adaptation

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.888424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 41ab69da-0dee-4b7c-9ace-2ab0f83acb02 · outbound

This paper cites Dropout as a bayesian approximation: Representing model uncertainty in deep learning.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Dropout as a bayesian approximation: Representing model uncertainty in deep learning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.905730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 05060f2b-5afa-430a-9781-b26c39646cd4 · outbound

This paper cites Domain-adversarial training of neural networks.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Domain-adversarial training of neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.880507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6213cc2b-938d-4003-afc9-a00edd3f186d · outbound

This paper cites Geodesic flow kernel for unsupervised domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Geodesic flow kernel for unsupervised domain adaptation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.884248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 7c52dcc0-c85c-496c-96cc-382765bc5895 · outbound

This paper cites Generative adversarial nets.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Generative adversarial nets

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.859377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 30a3e562-9023-4495-a22a-3b2dcfafd437 · outbound

This paper cites Practical variational inference for neural networks.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Practical variational inference for neural networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.844443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation f171952b-a71e-4c40-af0e-53fe3778eb4b · outbound

This paper cites C y CADA : Cycle-consistent adversarial domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation C y CADA : Cycle-consistent adversarial domain adaptation

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.848732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation fd730813-d5d5-415b-9add-149ae9579d35 · outbound

This paper cites Correcting sample selection bias by unlabeled data.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Correcting sample selection bias by unlabeled data

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.909892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation a5ceb9b2-3398-42bf-83cd-4a80faf0f10c · outbound

This paper cites What uncertainties do we need in bayesian deep learning for computer vision? In Advances in neural information processing systems , pages 5574--5584.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation What uncertainties do we need in bayesian deep learning for computer vision? In Advances in neural information processing systems , pages 5574--5584

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.872465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 1b0d6e12-0843-41f9-96a6-083449155b5c · outbound

This paper cites End-to-end adversarial memory network for cross-domain sentiment classification.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation End-to-end adversarial memory network for cross-domain sentiment classification

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.863844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 9bfac705-b1f9-4e3e-9082-b2af5aecb725 · outbound

This paper cites Deep transfer learning with joint adaptation networks.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Deep transfer learning with joint adaptation networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.876712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 40f18722-e417-403c-a428-c4f3e7ded94d · outbound

This paper cites Conditional adversarial domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Conditional adversarial domain adaptation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.892629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 45b0ce5e-5a57-4e9e-9990-a38538c1cb2e · outbound

This paper cites Visualizing data using t-sne.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Visualizing data using t-sne

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.954269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 99b6d422-ad90-4fc5-a9aa-57f7582a80a1 · outbound

This paper cites Multi-adversarial domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Multi-adversarial domain adaptation

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.959611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 4ed356c2-a27b-4ac7-a4c1-c736ac6eafe3 · outbound

This paper cites Adapting visual category models to new domains.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Adapting visual category models to new domains

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.964834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 968e0609-1062-4a89-9368-ed4c0e33319f · outbound

This paper cites A dirt-t approach to unsupervised domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation A dirt-t approach to unsupervised domain adaptation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.947202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 66f310ed-dd1f-4866-8eb5-7e01ed9495fd · outbound

This paper cites Dropout: a simple way to prevent neural networks from overfitting.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Dropout: a simple way to prevent neural networks from overfitting

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.934217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6b3381fc-fc25-477f-aabd-c7af542ee1d1 · outbound

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

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Deep coral: Correlation alignment for deep domain adaptation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.943292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation c67cdb4c-b1fd-4c0b-bd77-bde4a4979653 · outbound

This paper cites Adversarial discriminative domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Adversarial discriminative domain adaptation

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.938992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 72dcac2c-9765-45eb-b09e-fc9f33a2d727 · outbound

This paper cites Deep hashing network for unsupervised domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Deep hashing network for unsupervised domain adaptation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.919276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3021feeb-5b3d-457f-b702-a25bd459322f · outbound

This paper cites Exploiting local feature patterns for unsupervised domain adaptation.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Exploiting local feature patterns for unsupervised domain adaptation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.915114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 6df2f76b-335e-4d55-a184-b0624264f591 · outbound

This paper cites Tsang, Sinno Jialin Pan, and Mingkui Tan.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation Tsang, Sinno Jialin Pan, and Mingkui Tan

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.923235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 94f4f66f-bd96-4cad-9e10-c39b38e7bd37 · outbound

This paper cites write newline.

Bayesian Uncertainty Matching for Unsupervised Domain Adaptation write newline

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T17:51:07.927677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Pith citing papers

No inbound Pith citation observations are available.