References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

[2] ↑ Deep generative models for transductive transfer learning — author (P50): Jinyong Hou. wikidata.org.
[3] ↑ Deep generative models for transductive transfer learning — publisher (P123): OUR Archive. wikidata.org.
[4] ↑ Deep generative models for transductive transfer learning — language of work or name (P407): English. wikidata.org.
[5] ↑ Deep generative models for transductive transfer learning — country of origin (P495): New Zealand. wikidata.org.
[6] ↑ Deep generative models for transductive transfer learning — publication date (P577): 2021. wikidata.org.
[7] ↑ Deep generative models for transductive transfer learning — main subject (P921): transfer learning. wikidata.org.
[8] ↑ Deep generative models for transductive transfer learning — main subject (P921): deep learning. wikidata.org.
[9] ↑ Deep generative models for transductive transfer learning — title (P1476): Deep generative models for transductive transfer learning. wikidata.org.
[10] ↑ Deep generative models for transductive transfer learning — copyright holder (P3931): Jinyong Hou. wikidata.org.
[11] ↑ Deep generative models for transductive transfer learning — thesis submitted to (P4101): University of Otago. wikidata.org.
[12] ↑ Deep generative models for transductive transfer learning — on focus list of Wikimedia project (P5008): NZThesisProject. wikidata.org.
[13] ↑ Deep generative models for transductive transfer learning — copyright status (P6216): copyrighted. wikidata.org.
[14] ↑ Deep generative models for transductive transfer learning — thesis committee member (P9161): Jeremiah D Deng. wikidata.org.
[15] ↑ Deep generative models for transductive transfer learning — thesis committee member (P9161): Stephen Cranefield. wikidata.org.
[16] ↑ Deep generative models for transductive transfer learning — thesis submitted for degree (P13338): Doctor of Philosophy. wikidata.org.

Class ancestry

[1] ↑ Deep generative models for transductive transfer learning is an instance of doctoral thesis (Q187685) [P31, primary]. Wikidata. wikidata.org.

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@misc{4ortxyz_deep-generative-models-for-transductive-transfer-learning_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Deep generative models for transductive transfer learning}}, year = {2026}, url = {https://4ort.xyz/entity/deep-generative-models-for-transductive-transfer-learning}, note = {Accessed: 2026-05-03}}

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According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Deep generative models for transductive transfer learning — https://4ort.xyz/entity/deep-generative-models-for-transductive-transfer-learning (retrieved 2026-05-03)

Canonical URL: https://4ort.xyz/entity/deep-generative-models-for-transductive-transfer-learning · Last refreshed: May 3, 2026

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Rolling log of changes to this entity's Wikidata record. Values shown reflect the current state of each edited property — follow the history link to see the precise diff for any edit.

8w ago · DrThneed · 2026-09-06 view diff on Wikidata ↗

Thesis submitted for degree → Doctor of Philosophy

Thesis submitted to → University of Otago

Handle ID → 10523/12113

Copyright status → copyrighted

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"/* wbeditentity-update:0| */ QuickStatements 3.0 [[:toollabs:qs-dev/batch/52327|batch #52327]]: Otago"

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Deep generative models for transductive transfer learning

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