Peter Battaglia
Peter Battaglia
Research Scientist, DeepMind
Verified email at
TitleCited byYear
Bayesian integration of visual and auditory signals for spatial localization
PW Battaglia, RA Jacobs, RN Aslin
Josa a 20 (7), 1391-1397, 2003
A simple neural network module for relational reasoning
A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ...
Advances in neural information processing systems, 4967-4976, 2017
Simulation as an engine of physical scene understanding
PW Battaglia, JB Hamrick, JB Tenenbaum
Proceedings of the National Academy of Sciences 110 (45), 18327-18332, 2013
Relational inductive biases, deep learning, and graph networks
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
arXiv preprint arXiv:1806.01261, 2018
Interaction networks for learning about objects, relations and physics
P Battaglia, R Pascanu, M Lai, DJ Rezende, K Kavukcuoglu
Advances in Neural Information Processing Systems 2016, 4502-4510, 2016
Unsupervised learning of 3d structure from images
DJ Rezende, SMA Eslami, S Mohamed, P Battaglia, M Jaderberg, ...
Advances in Neural Information Processing Systems, 4996-5004, 2016
Imagination-augmented agents for deep reinforcement learning
T Weber, S Racanière, DP Reichert, L Buesing, A Guez, DJ Rezende, ...
arXiv preprint arXiv:1707.06203, 2017
Humans trade off viewing time and movement duration to improve visuomotor accuracy in a fast reaching task
PW Battaglia, PR Schrater
Journal of Neuroscience 27 (26), 6984-6994, 2007
Visual interaction networks: Learning a physics simulator from video
N Watters, D Zoran, T Weber, P Battaglia, R Pascanu, A Tacchetti
Advances in neural information processing systems, 4539-4547, 2017
Learning deep generative models of graphs
Y Li, O Vinyals, C Dyer, R Pascanu, P Battaglia
arXiv preprint arXiv:1803.03324, 2018
Humans predict liquid dynamics using probabilistic simulation.
C Bates, P Battaglia, I Yildirim, JB Tenenbaum
CogSci, 2015
Internal physics models guide probabilistic judgments about object dynamics
J Hamrick, P Battaglia, JB Tenenbaum
Proceedings of the 33rd annual conference of the cognitive science society 2, 2011
Graph networks as learnable physics engines for inference and control
A Sanchez-Gonzalez, N Heess, JT Springenberg, J Merel, M Riedmiller, ...
arXiv preprint arXiv:1806.01242, 2018
Imagination-augmented agents for deep reinforcement learning
S Racanière, T Weber, D Reichert, L Buesing, A Guez, DJ Rezende, ...
Advances in neural information processing systems, 5690-5701, 2017
How haptic size sensations improve distance perception
PW Battaglia, D Kersten, PR Schrater
PLoS computational biology 7 (6), e1002080, 2011
Relevant and robust: A response to Marcus and Davis (2013)
ND Goodman, MC Frank, TL Griffiths, JB Tenenbaum, PW Battaglia, ...
Psychological science 26 (4), 539-541, 2015
Inferring mass in complex scenes by mental simulation
JB Hamrick, PW Battaglia, TL Griffiths, JB Tenenbaum
Cognition 157, 61-76, 2016
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
Discovering objects and their relations from entangled scene representations
D Raposo, A Santoro, D Barrett, R Pascanu, T Lillicrap, P Battaglia
arXiv preprint arXiv:1702.05068, 2017
Learning to perform physics experiments via deep reinforcement learning
M Denil, P Agrawal, TD Kulkarni, T Erez, P Battaglia, N de Freitas
arXiv preprint arXiv:1611.01843, 2016
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