Elamur Research⌕
☰
home / authors / David G. T. Barrett

David G. T. Barrett

David G. T. Barrett has 2 papers in our library, in 2017–2018, most of them on Reasoning; often with Adam Santoro, Timothy Lillicrap, Ari S. Morcos.

2 papers in our library · 2017–2018

OpenAlex · ORCID · h-index 15 · 48 works · 1,710 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 281 times in our library · ⭐ Paper Stars ranking: #3135

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢Google DeepMindLondon · United Kingdom2017–2026 · 13 paperscurrent🏢GoogleMountain View · United States2017–2021 · 6 papers🔬École Normale Supérieure - PSLParis · France2012–2016 · 6 papers🔬Champalimaud FoundationLisbon · Portugal2013–2016 · 4 papers🔬Laboratoire de Neurosciences CognitivesParis · France2015–2016 · 3 papers🎓Trinity College DublinDublin · Ireland2007–2009 · 2 papers🏢GoogleDublin · IrelandEmployment

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksArts and Humanities · 1 workComputer Vision and Pattern Recognition · 1 workLanguage and Linguistics · 1 work

🧭 Topics 1Research subjects and languages the work is about.Reasoning · 2 works

 Works by year

2010s

20181 paper20171 paper

 Papers

The most cited first (OpenAlex and our library).

  1. A simple neural network module for relational reasoning (2017 · 632 citations)
    Networks such as CNNs and MLPs often fail on questions that depend on how several entities relate. Symbolic systems handle relations well but are brittle and hard to ground in raw input. The authors propose the Relation Network (RN), a small, fully differentiable module. It takes a set of "objects," applies one…
  2. Measuring abstract reasoning in neural networks (2018 · 173 citations)
    The authors from DeepMind examine whether neural networks truly learn to reason abstractly or merely exploit superficial statistical regularities in the data.

 Co-authors here

8 co-authors with a page, the most papers together first.

 Cited by

Papers of our library cite their works 281 times (of the 149,439 papers whose bibliographies we read); 51 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/david-g-t-barrett/