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David G. T. Barrett
Person information
- affiliation: Google DeepMind, London, UK
- affiliation: University of Cambridge, Department of Engineering, UK
- affiliation: ENS Paris, Group for Neural Theory, France
- affiliation (PhD 2012): University College London, UK
Other persons with the same name
- David Barrett — disambiguation page
- David Barrett 0002 — Franklin W. Olin College, Needham, MA, USA
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2020 – today
- 2024
- [i20]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 abs/2404.18416 (2024) - [i19]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 abs/2405.03162 (2024) - 2023
- [i18]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 abs/2304.05823 (2023) - [i17]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 abs/2311.18260 (2023) - 2022
- [c15]Benoit Dherin, Michael Munn, Mihaela Rosca, David Barrett:
Why neural networks find simple solutions: The many regularizers of geometric complexity. NeurIPS 2022 - [i16]Benoit Dherin, Michael Munn, Mihaela Rosca, David G. T. Barrett:
Why neural networks find simple solutions: the many regularizers of geometric complexity. CoRR abs/2209.13083 (2022) - 2021
- [c14]David G. T. Barrett, Benoit Dherin:
Implicit Gradient Regularization. ICLR 2021 - [c13]Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De:
On the Origin of Implicit Regularization in Stochastic Gradient Descent. ICLR 2021 - [c12]Mihaela Rosca, Yan Wu, Benoit Dherin, David Barrett:
Discretization Drift in Two-Player Games. ICML 2021: 9064-9074 - [i15]Samuel L. Smith, Benoit Dherin, David G. T. Barrett, Soham De:
On the Origin of Implicit Regularization in Stochastic Gradient Descent. CoRR abs/2101.12176 (2021) - [i14]Mihaela Rosca, Yan Wu, Benoit Dherin, David G. T. Barrett:
Discretization Drift in Two-Player Games. CoRR abs/2105.13922 (2021) - [i13]Benoit Dherin, Michael Munn, David G. T. Barrett:
The Geometric Occam's Razor Implicit in Deep Learning. CoRR abs/2111.15090 (2021) - 2020
- [c11]David Barrett, Felix Hill, Adam Santoro, Jay McClelland:
Cognitive consequences of structured education in a connectionist model of analogical reasoning. CogSci 2020 - [c10]Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David G. T. Barrett, Marta Garnelo:
An Explicitly Relational Neural Network Architecture. ICML 2020: 8593-8603 - [i12]David G. T. Barrett, Benoit Dherin:
Implicit Gradient Regularization. CoRR abs/2009.11162 (2020)
2010 – 2019
- 2019
- [c9]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 - [c8]David Pfau, Stig Petersen, Ashish Agarwal, David G. T. Barrett, Kimberly L. Stachenfeld:
Spectral Inference Networks: Unifying Deep and Spectral Learning. ICLR (Poster) 2019 - [i11]Felix Hill, Adam Santoro, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap:
Learning to Make Analogies by Contrasting Abstract Relational Structure. CoRR abs/1902.00120 (2019) - [i10]Adam Santoro, Felix Hill, David G. T. Barrett, David Raposo, Matthew M. 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 abs/1904.10396 (2019) - [i9]Murray Shanahan, Kyriacos Nikiforou, Antonia Creswell, Christos Kaplanis, David Barrett, Marta Garnelo:
An Explicitly Relational Neural Network Architecture. CoRR abs/1905.10307 (2019) - 2018
- [c7]Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick:
On the importance of single directions for generalization. ICLR (Poster) 2018 - [c6]Adam Santoro, Felix Hill, David G. T. Barrett, Ari S. Morcos, Timothy P. Lillicrap:
Measuring abstract reasoning in neural networks. ICML 2018: 4477-4486 - [i8]Ari S. Morcos, David G. T. Barrett, Neil C. Rabinowitz, Matthew M. Botvinick:
On the importance of single directions for generalization. CoRR abs/1803.06959 (2018) - [i7]David Pfau, Stig Petersen, Ashish Agarwal, David G. T. Barrett, Kimberly L. Stachenfeld:
Spectral Inference Networks: Unifying Spectral Methods With Deep Learning. CoRR abs/1806.02215 (2018) - [i6]David G. T. Barrett, Felix Hill, Adam Santoro, Ari S. Morcos, Timothy P. Lillicrap:
Measuring abstract reasoning in neural networks. CoRR abs/1807.04225 (2018) - [i5]David G. T. Barrett, Ari S. Morcos, Jakob H. Macke:
Analyzing biological and artificial neural networks: challenges with opportunities for synergy? CoRR abs/1810.13373 (2018) - 2017
- [c5]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 - [c4]Samuel Ritter, David G. T. Barrett, Adam Santoro, Matt M. Botvinick:
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study. ICML 2017: 2940-2949 - [c3]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: 4967-4976 - [i4]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 abs/1702.05068 (2017) - [i3]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 abs/1706.01427 (2017) - [i2]Samuel Ritter, David G. T. Barrett, Adam Santoro, Matthew M. Botvinick:
Cognitive Psychology for Deep Neural Networks: A Shape Bias Case Study. CoRR abs/1706.08606 (2017) - [i1]Matthew M. 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 abs/1711.08378 (2017) - 2013
- [c2]David G. T. Barrett, Sophie Denève, Christian K. Machens:
Firing rate predictions in optimal balanced networks. NIPS 2013: 1538-1546 - 2012
- [c1]Ralph Bourdoukan, David G. T. Barrett, Christian K. Machens, Sophie Denève:
Learning optimal spike-based representations. NIPS 2012: 2294-2302
Coauthor Index
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last updated on 2024-07-09 21:15 CEST by the dblp team
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