David G. T. Barrett

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 29

Top Topics

Steepest Ascent

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Publications

Lin Yang, Shawn Xu, Andrew Sellergren, Timo Kohlberger, Yuchen Zhou, Ira Ktena, Atilla P. Kiraly, Faruk Ahmed, Farhad Hormozdiari, Tiam Jaroensri, Eric Wang, Ellery Wulczyn, Fayaz Jamil, Theo Guidroz, Chuck Lau, Siyuan Qiao, Yun Liu, Akshay Goel, Kendall Park, Arnav Agharwal, Nick George, Yang Wang, Ryutaro Tanno, David G. T. Barrett, Wei-Hung Weng, S. Sara Mahdavi, Khaled Saab, Tao Tu, Sreenivasa Raju Kalidindi, Mozziyar Etemadi, Jorge Cuadros, Gregory Sorensen, Yossi Matias, Katherine Chou, Greg Corrado, Joelle K. Barral, Shravya Shetty, David J. Fleet, S. M. Ali Eslami, Daniel Tse, Shruthi Prabhakara, Cory Y. McLean, Dave Steiner, Rory Pilgrim, Christopher Kelly, Shekoofeh Azizi, Daniel Golden
Advancing Multimodal Medical Capabilities of Gemini. CoRR (2024)
Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno, David Stutz, Ellery Wulczyn, Fan Zhang, Tim Strother, Chunjong Park, Elahe Vedadi, Juanma Zambrano Chaves, Szu-Yeu Hu, Mike Schaekermann, Aishwarya Kamath, Yong Cheng, David G. T. Barrett, Cathy Cheung, Basil Mustafa, Anil Palepu, Daniel McDuff, Le Hou, Tomer Golany, Luyang Liu, Jean-Baptiste Alayrac, Neil Houlsby, Nenad Tomasev, Jan Freyberg, Charles Lau, Jonas Kemp, Jeremy Lai, Shekoofeh Azizi, Kimberly Kanada, SiWai Man, Kavita Kulkarni, Ruoxi Sun, Siamak Shakeri, Luheng He, Benjamin Caine, Albert Webson, Natasha Latysheva, Melvin Johnson, Philip Andrew Mansfield, Jian Lu, Ehud Rivlin, Jesper Anderson, Bradley Green, Renee Wong, Jonathan Krause, Jonathon Shlens, Ewa Dominowska, S. M. Ali Eslami, Katherine Chou, Claire Cui, Oriol Vinyals, Koray Kavukcuoglu, James Manyika, Jeff Dean, Demis Hassabis, Yossi Matias, Dale R. Webster, Joelle K. Barral, Greg Corrado, Christopher Semturs, S. Sara Mahdavi, Juraj Gottweis, Alan Karthikesalingam, Vivek Natarajan
Capabilities of Gemini Models in Medicine. CoRR (2024)
Ryutaro Tanno, David G. T. Barrett, Andrew Sellergren, Sumedh Ghaisas, Sumanth Dathathri, Abigail See, Johannes Welbl, Karan Singhal, Shekoofeh Azizi, Tao Tu, Mike Schaekermann, Rhys May, Roy Lee, SiWai Man, Zahra Ahmed, S. Sara Mahdavi, Danielle Belgrave, Vivek Natarajan, Shravya Shetty, Pushmeet Kohli, Po-Sen Huang, Alan Karthikesalingam, Ira Ktena
Consensus, dissensus and synergy between clinicians and specialist foundation models in radiology report generation. 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)
Benoit Dherin, Michael Munn, Mihaela Rosca, David G. T. Barrett
Why neural networks find simple solutions: the many regularizers of geometric complexity. CoRR (2022)
Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De
On the Origin of Implicit Regularization in Stochastic Gradient Descent. ICLR (2021)
Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De
On the Origin of Implicit Regularization in Stochastic Gradient Descent. CoRR (2021)
David G. T. Barrett, Benoit Dherin
Implicit Gradient Regularization. ICLR (2021)
Benoit Dherin, Micheal Munn, David G. T. Barrett
The Geometric Occam's Razor Implicit in Deep Learning. CoRR (2021)
Mihaela Rosca, Yan Wu, Benoit Dherin, David G. T. Barrett
Discretization Drift in Two-Player Games. CoRR (2021)
Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David G. T. Barrett, Marta Garnelo
An Explicitly Relational Neural Network Architecture. ICML (2020)
David G. T. Barrett, Benoit Dherin
Implicit Gradient Regularization. CoRR (2020)
David Pfau, Stig Petersen, Ashish Agarwal, David G. T. Barrett, Kimberly L. Stachenfeld
Spectral Inference Networks: Unifying Deep and Spectral Learning. ICLR (Poster) (2019)
Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap
Learning to Make Analogies by Contrasting Abstract Relational Structure. CoRR (2019)
Adam Santoro, Felix Hill, David G. T. Barrett, David Raposo, Matthew Botvinick, Timothy P. Lillicrap
Is coding a relevant metaphor for building AI? A commentary on "Is coding a relevant metaphor for the brain?", by Romain Brette. CoRR (2019)
Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap
Learning to Make Analogies by Contrasting Abstract Relational Structure. ICLR (Poster) (2019)
David G. T. Barrett, Ari S. Morcos, Jakob H. Macke
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? CoRR (2018)
Adam Santoro, Felix Hill, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap
Measuring abstract reasoning in neural networks. ICML (2018)
David Pfau, Stig Petersen, Ashish Agarwal, David G. T. Barrett, Kimberly L. Stachenfeld
Spectral Inference Networks: Unifying Spectral Methods With Deep Learning. CoRR (2018)
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew Botvinick
On the importance of single directions for generalization. ICLR (Poster) (2018)
Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew Botvinick
On the importance of single directions for generalization. CoRR (2018)
David G. T. Barrett, Felix Hill, Adam Santoro, Ari S. Morcos, Timothy P. Lillicrap
Measuring abstract reasoning in neural networks. CoRR (2018)
David Raposo, Adam Santoro, David G. T. Barrett, Razvan Pascanu, Timothy P. Lillicrap, Peter W. Battaglia
Discovering objects and their relations from entangled scene representations. CoRR (2017)
Adam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter W. Battaglia, Tim Lillicrap
A simple neural network module for relational reasoning. NIPS (2017)
Matthew Botvinick, David G. T. Barrett, Peter W. Battaglia, Nando de Freitas, Dharshan Kumaran, Joel Z. Leibo, Tim Lillicrap, Joseph Modayil, S. Mohamed, Neil C. Rabinowitz, Danilo Jimenez Rezende, Adam Santoro, Tom Schaul, Christopher Summerfield, Greg Wayne, Theophane Weber, Daan Wierstra, Shane Legg, Demis Hassabis
Building Machines that Learn and Think for Themselves: Commentary on Lake et al., Behavioral and Brain Sciences, 2017. CoRR (2017)
Samuel Ritter, David G. T. Barrett, Adam Santoro, Matt M. Botvinick
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study. ICML (2017)
David Raposo, Adam Santoro, David G. T. Barrett, Razvan Pascanu, Tim Lillicrap, Peter W. Battaglia
Discovering objects and their relations from entangled scene representations. ICLR (Workshop) (2017)
Adam Santoro, David Raposo, David G. T. Barrett, Mateusz Malinowski, Razvan Pascanu, Peter W. Battaglia, Timothy P. Lillicrap
A simple neural network module for relational reasoning. CoRR (2017)
Samuel Ritter, David G. T. Barrett, Adam Santoro, Matthew Botvinick
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study. CoRR (2017)
David G. T. Barrett, Sophie Denève, Christian K. Machens
Firing rate predictions in optimal balanced networks. NIPS (2013)
Ralph Bourdoukan, David G. T. Barrett, Christian K. Machens, Sophie Denève
Learning optimal spike-based representations. NIPS (2012)