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Thomas Unterthiner

researcher ORCID ID = 0000-0001-5361-3087
Person human Q59559841

Facts

6 properties
Instance of
human
Sex or gender
male[2]
Occupation
researcher
Official website
bioinf.jku.at[4]
Given name
Thomas[3]
Imported from
wholeness_audit_2026-05-02
🏷️ Also known as
en Thomas Unterthiner
🔖 Identifiers · 9
ORCID iD
0000-0001-5361-3087
OpenAlex ID
A5083016682as of 2026-09-23
where from?
Source
OpenAlex
Edition
20260923 · as of 2026-09-23
Bronze
not in the catalog
Transform
4ort-mint · openalex:20260923 · version not recorded
DBLP author ID
50/9446
Google Scholar author ID
QCARd5gAAAAJ
OpenReview.net profile ID
Thomas_Unterthiner1
ResearchGate profile ID
Thomas-Unterthiner
ResearcherID
K-7231-2018
Scopus author ID
37078167900
X (Twitter) username
TomUnterthiner (2009–present)

Report an error or request removal Lineage (PROV-JSON)

📜 Data licence
Source: OpenAlex (openalex.org), snapshot of 2026-09-23. CC0 1.0 Universal. CC0 1.0 Universal · OpenAlex
🔗 Connections
Author of 10
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments, Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields, DeepTox: Toxicity Prediction using Deep Learning, GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium, Large-scale comparison of machine learning methods for drug target prediction on ChEMBL, Object-Centric Learning with Slot Attention, RUDDER: Return Decomposition for Delayed Rewards +2 more
← Authored by 10
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale, Biomolecular dynamics with machine-learned quantum-mechanical force fields trained on diverse chemical fragments, Coulomb GANs: Provably Optimal Nash Equilibria via Potential Fields, DeepTox: Toxicity Prediction using Deep Learning, GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium, Large-scale comparison of machine learning methods for drug target prediction on ChEMBL, Object-Centric Learning with Slot Attention, RUDDER: Return Decomposition for Delayed Rewards +2 more
Affiliated with 5
Google, Johannes Kepler University Linz, Bioinformatics Institute, Google (Switzerland), RISC Software GmbH (Austria)
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Summary

Thomas Unterthiner worked as a researcher[1].

FAQs

What did Thomas Unterthiner do for work?

Thomas Unterthiner worked as researcher[1].

Related Entities

Bioinformatics Institute Google

References

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

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.
  2. [1] ↑ . wikidata.org.
  3. [3] ↑ . wikidata.org.
  4. [4] ↑ . ORCID Public Data File 2020. Retrieved . pub.orcid.org. Provenance: wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). Thomas Unterthiner. Retrieved October 24, 2026, from https://4ort.xyz/entity/thomas-unterthiner
MLA “Thomas Unterthiner.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 Oct. 2026, https://4ort.xyz/entity/thomas-unterthiner.
BibTeX @misc{4ortxyz_thomas-unterthiner_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Thomas Unterthiner}}, year = {2026}, url = {https://4ort.xyz/entity/thomas-unterthiner}, note = {Accessed: 2026-10-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Thomas Unterthiner — https://4ort.xyz/entity/thomas-unterthiner (retrieved 2026-10-24)

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