Thomas D. Barrett

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 18

Top Topics

Combinatorial Optimization

Reinforcement Learning

Top Venues

Publications

Benoit Gaujac, Jérémie Donà, Liviu Copoiu, Timothy Atkinson, Thomas Pierrot, Thomas D. Barrett
Learning the Language of Protein Structure. CoRR (2024)
Félix Chalumeau, Refiloe Shabe, Noah de Nicola, Arnu Pretorius, Thomas D. Barrett, Nathan Grinsztajn
Memory-Enhanced Neural Solvers for Efficient Adaptation in Combinatorial Optimization. CoRR (2024)
Amelia Villegas-Morcillo, Louis Robinson, Arthur Flajolet, Thomas D. Barrett
ManyFold: an efficient and flexible library for training and validating protein folding models. Bioinform. 39 (1) (2023)
Christopher W. F. Parsonson, Alexandre Laterre, Thomas D. Barrett
Reinforcement Learning for Branch-and-Bound Optimisation Using Retrospective Trajectories. AAAI (2023)
Félix Chalumeau, Shikha Surana, Clément Bonnet, Nathan Grinsztajn, Arnu Pretorius, Alexandre Laterre, Thomas D. Barrett
Combinatorial Optimization with Policy Adaptation using Latent Space Search. CoRR (2023)
Andries P. Smit, Paul Duckworth, Nathan Grinsztajn, Kale-ab Tessera, Thomas D. Barrett, Arnu Pretorius
Are we going MAD? Benchmarking Multi-Agent Debate between Language Models for Medical Q&A. CoRR (2023)
Thomas D. Barrett, Christopher W. F. Parsonson, Alexandre Laterre
Learning to Solve Combinatorial Graph Partitioning Problems via Efficient Exploration. CoRR (2022)
Matthew Morris, Thomas D. Barrett, Arnu Pretorius
Universally Expressive Communication in Multi-Agent Reinforcement Learning. CoRR (2022)
Christopher W. F. Parsonson, Alexandre Laterre, Thomas D. Barrett
Reinforcement Learning for Branch-and-Bound Optimisation using Retrospective Trajectories. CoRR (2022)
Matthew Morris, Thomas D. Barrett, Arnu Pretorius
Universally Expressive Communication in Multi-Agent Reinforcement Learning. NeurIPS (2022)
Thomas D. Barrett, Aleksei Malyshev, A. I. Lvovsky
Autoregressive neural-network wavefunctions for ab initio quantum chemistry. Nat. Mach. Intell. 4 (4) (2022)
Nathan Grinsztajn, Daniel Furelos-Blanco, Thomas D. Barrett
Population-Based Reinforcement Learning for Combinatorial Optimization. CoRR (2022)
Thomas D. Barrett, Aleksei Malyshev, A. I. Lvovsky
Autoregressive neural-network wavefunctions for ab initio quantum chemistry. CoRR (2021)
Robin Quessard, Thomas D. Barrett, William R. Clements
Learning Disentangled Representations and Group Structure of Dynamical Environments. NeurIPS (2020)
Thomas D. Barrett, William R. Clements, Jakob N. Foerster, A. I. Lvovsky
Exploratory Combinatorial Optimization with Reinforcement Learning. AAAI (2020)
Robin Quessard, Thomas D. Barrett, William R. Clements
Learning Group Structure and Disentangled Representations of Dynamical Environments. CoRR (2020)
Thomas D. Barrett, William R. Clements, Jakob N. Foerster, A. I. Lvovsky
Exploratory Combinatorial Optimization with Reinforcement Learning. CoRR (2019)
Xianxin Guo, Thomas D. Barrett, Zhiming M. Wang, A. I. Lvovsky
End-to-end optical backpropagation for training neural networks. CoRR (2019)