Thomas D Barrett

Thomas D Barrett

University of Oxford

H-index: 9

Europe-United Kingdom

About Thomas D Barrett

Thomas D Barrett, With an exceptional h-index of 9 and a recent h-index of 9 (since 2020), a distinguished researcher at University of Oxford, specializes in the field of Machine Learning, Reinforcement Learning, Computational Biology, Quantum Machine Learning, Quantum Optics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Combinatorial optimization with policy adaptation using latent space search

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

Contrasting Sequence with Structure: Pre-training Graph Representations with PLMs

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A

Bursts of polarised single photons from atom-cavity sources

Reinforcement learning for branch-and-bound optimisation using retrospective trajectories

ManyFold: an efficient and flexible library for training and validating protein folding models

Universally expressive communication in multi-agent reinforcement learning

Thomas D Barrett Information

University

Position

Postdoctoral Research Assistant

Citations(all)

482

Citations(since 2020)

481

Cited By

54

hIndex(all)

9

hIndex(since 2020)

9

i10Index(all)

8

i10Index(since 2020)

8

Email

University Profile Page

University of Oxford

Google Scholar

View Google Scholar Profile

Thomas D Barrett Skills & Research Interests

Machine Learning

Reinforcement Learning

Computational Biology

Quantum Machine Learning

Quantum Optics

Top articles of Thomas D Barrett

Title

Journal

Author(s)

Publication Date

Combinatorial optimization with policy adaptation using latent space search

Advances in Neural Information Processing Systems

Felix Chalumeau

Shikha Surana

Clément Bonnet

Nathan Grinsztajn

Arnu Pretorius

...

2024/2/13

Winner Takes It All: Training Performant RL Populations for Combinatorial Optimization

Nathan Grinsztajn

Daniel Furelos-Blanco

Shikha Surana

Clément Bonnet

Thomas D Barrett

2023/11/2

Contrasting Sequence with Structure: Pre-training Graph Representations with PLMs

bioRxiv

Louis Robinson

Timothy Atkinson

Liviu Copoiu

Patrick Bordes

Thomas Pierrot

...

2023/12/4

Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A

Andries Smit

Paul Duckworth

Nathan Grinsztajn

Kale-ab Tessera

Thomas Barrett

...

2023/10/27

Bursts of polarised single photons from atom-cavity sources

Journal of Physics B: Atomic, Molecular and Optical Physics

Jan Ole Ernst

Juan Rafael Alvarez

Thomas D Barrett

Axel Kuhn

2023/9/25

Reinforcement learning for branch-and-bound optimisation using retrospective trajectories

Proceedings of the AAAI Conference on Artificial Intelligence

Christopher WF Parsonson

Alexandre Laterre

Thomas D Barrett

2023/6/26

ManyFold: an efficient and flexible library for training and validating protein folding models

Bioinformatics

Amelia Villegas-Morcillo

Louis Robinson

Arthur Flajolet

Thomas D Barrett

2023/1

Universally expressive communication in multi-agent reinforcement learning

Advances in Neural Information Processing Systems

Matthew Morris

Thomas D Barrett

Arnu Pretorius

2022/12/6

So manyfolds, so little time: efficient protein structure prediction with pLMs and MSAs

bioRxiv

Thomas D Barrett

Amelia Villegas-Morcillo

Louis Robinson

Benoit Gaujac

David Adméte

...

2022/10/18

Polarized single photons from a cavity-enhanced atom-light interface with coherent re-preparation

Jan Ole Ernst

Juan-Rafael Álvarez

Thomas D Barrett

Axel Kuhn

2022/6/13

Learning to solve combinatorial graph partitioning problems via efficient exploration

arXiv preprint arXiv:2205.14105

Thomas D Barrett

Christopher WF Parsonson

Alexandre Laterre

2022/5/27

Autoregressive neural-network wavefunctions for ab initio quantum chemistry

Nature Machine Intelligence

Thomas D Barrett

Aleksei Malyshev

AI Lvovsky

2022/4

How to administer an antidote to Schrödinger’s cat

Journal of Physics B: Atomic, Molecular and Optical Physics

Juan-Rafael Álvarez

Mark IJspeert

Oliver Barter

Ben Yuen

Thomas D Barrett

...

2022/3/17

One step at a time: Pros and cons of multi-step meta-gradient reinforcement learning

arXiv preprint arXiv:2111.00206

Clément Bonnet

Paul Caron

Thomas Barrett

Ian Davies

Alexandre Laterre

2021/10/30

Backpropagation through nonlinear units for the all-optical training of neural networks

Photonics Research

Xianxin Guo

Thomas D Barrett

Zhiming M Wang

AI Lvovsky

2021/3/1

Learning disentangled representations and group structure of dynamical environments

Advances in Neural Information Processing Systems

Robin Quessard

Thomas Barrett

William Clements

2020

Fully reconfigurable coherent optical vector–matrix multiplication

Optics Letters

James Spall

Xianxin Guo

Thomas D Barrett

AI Lvovsky

2020/10/15

Pushing Purcell enhancement beyond its limits

New Journal of Physics

Thomas D Barrett

Thomas H Doherty

Axel Kuhn

2020/6/15

Exploratory combinatorial optimization with reinforcement learning

Proceedings of the AAAI conference on artificial intelligence

Thomas Barrett

William Clements

Jakob Foerster

Alex Lvovsky

2020/4/3

See List of Professors in Thomas D Barrett University(University of Oxford)

Co-Authors

H-index: 174
Dustin Stuart

Dustin Stuart

University of Oxford

H-index: 56
A.I. Lvovsky

A.I. Lvovsky

University of Oxford

H-index: 33
Axel Kuhn

Axel Kuhn

University of Oxford

H-index: 11
Xianxin Guo

Xianxin Guo

University of Oxford

H-index: 2
Robin Quessard

Robin Quessard

École Normale Supérieure

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