Matthew M. Botvinick

Publication Activity (10 Years)

Years Active: 2001-2023
Publications (10 Years): 20

Top Topics

Maximum A Posteriori

Generalized Gaussian

Reinforcement Learning

Top Venues

Publications

Nathan J. Wispinski, Andrew Butcher, Kory Wallace Mathewson, Craig S. Chapman, Matthew M. Botvinick, Patrick M. Pilarski
Adaptive patch foraging in deep reinforcement learning agents. Trans. Mach. Learn. Res. 2023 (2023)
Julian Coda-Forno, Marcel Binz, Zeynep Akata, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
Meta-in-context learning in large language models. CoRR (2023)
Marcel Binz, Stephan Alaniz, Adina Roskies, Balazs Aczel, Carl T. Bergstrom, Colin Allen, Daniel Schad, Dirk Wulff, Jevin D. West, Qiong Zhang, Richard M. Shiffrin, Samuel J. Gershman, Ven Popov, Emily M. Bender, Marco Marelli, Matthew M. Botvinick, Zeynep Akata, Eric Schulz
How should the advent of large language models affect the practice of science? CoRR (2023)
Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. ICLR (2023)
Marcel Binz, Ishita Dasgupta, Akshay Jagadish, Matthew M. Botvinick, Jane X. Wang, Eric Schulz
Meta-Learned Models of Cognition. CoRR (2023)
Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
Michiel A. Bakker, Martin J. Chadwick, Hannah R. Sheahan, Michael Henry Tessler, Lucy Campbell-Gillingham, Jan Balaguer, Nat McAleese, Amelia Glaese, John Aslanides, Matthew M. Botvinick, Christopher Summerfield
Fine-tuning language models to find agreement among humans with diverse preferences. CoRR (2022)
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira
Perceiver IO: A General Architecture for Structured Inputs & Outputs. ICLR (2022)
Patrick M. Pilarski, Andrew Butcher, Elnaz Davoodi, Michael Bradley Johanson, Dylan J. A. Brenneis, Adam S. R. Parker, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White
The Frost Hollow Experiments: Pavlovian Signalling as a Path to Coordination and Communication Between Agents. CoRR (2022)
Daniel C. McNamee, Kimberly L. Stachenfeld, Matthew M. Botvinick, Samuel J. Gershman
Compositional Sequence Generation in the Entorhinal-Hippocampal System. Entropy 24 (12) (2022)
Nathan J. Wispinski, Andrew Butcher, Kory W. Mathewson, Craig S. Chapman, Matthew M. Botvinick, Patrick M. Pilarski
Adaptive patch foraging in deep reinforcement learning agents. CoRR (2022)
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. CoRR (2022)
Ted Moskovitz, Ta-Chu Kao, Maneesh Sahani, Matthew M. Botvinick
Minimum Description Length Control. CoRR (2022)
Anthony Zador, Blake A. Richards, Bence Ölveczky, Sean Escola, Yoshua Bengio, Kwabena Boahen, Matthew M. Botvinick, Dmitri B. Chklovskii, Anne Churchland, Claudia Clopath, James DiCarlo, Surya Ganguli, Jeff Hawkins, Konrad P. Körding, Alexei A. Koulakov, Yann LeCun, Timothy P. Lillicrap, Adam H. Marblestone, Bruno A. Olshausen, Alexandre Pouget, Cristina Savin, Terrence J. Sejnowski, Eero P. Simoncelli, Sara A. Solla, David Sussillo, Andreas S. Tolias, Doris Tsao
Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution. CoRR (2022)
Curtis Hawthorne, Andrew Jaegle, Catalina Cangea, Sebastian Borgeaud, Charlie Nash, Mateusz Malinowski, Sander Dieleman, Oriol Vinyals, Matthew M. Botvinick, Ian Simon, Hannah Sheahan, Neil Zeghidour, Jean-Baptiste Alayrac, João Carreira, Jesse H. Engel
General-purpose, long-context autoregressive modeling with Perceiver AR. ICML (2022)
Dylan J. A. Brenneis, Adam S. R. Parker, Michael Bradley Johanson, Andrew Butcher, Elnaz Davoodi, Leslie Acker, Matthew M. Botvinick, Joseph Modayil, Adam White, Patrick M. Pilarski
Assessing Human Interaction in Virtual Reality With Continually Learning Prediction Agents Based on Reinforcement Learning Algorithms: A Pilot Study. CoRR (2021)
Andrew Jaegle, Sebastian Borgeaud, Jean-Baptiste Alayrac, Carl Doersch, Catalin Ionescu, David Ding, Skanda Koppula, Daniel Zoran, Andrew Brock, Evan Shelhamer, Olivier J. Hénaff, Matthew M. Botvinick, Andrew Zisserman, Oriol Vinyals, João Carreira
Perceiver IO: A General Architecture for Structured Inputs & Outputs. CoRR (2021)
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. ICLR (2020)
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin A. Riedmiller, Matthew M. Botvinick
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control. CoRR (2019)
Emilio Parisotto, H. Francis Song, Jack W. Rae, Razvan Pascanu, Çaglar Gülçehre, Siddhant M. Jayakumar, Max Jaderberg, Raphael Lopez Kaufman, Aidan Clark, Seb Noury, Matthew M. Botvinick, Nicolas Heess, Raia Hadsell
Stabilizing Transformers for Reinforcement Learning. CoRR (2019)
Vincent van Veen, Jonathan D. Cohen, Matthew M. Botvinick, V. Andrew Stenger, Cameron S. Carter
Anterior Cingulate Cortex, Conflict Monitoring, and Levels of Processing. NeuroImage 14 (6) (2001)