Vinicius Zambaldi
Vinicius Zambaldi
Google Deepmind
Verified email at google.com
TitleCited byYear
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
4122018
Multi-agent reinforcement learning in sequential social dilemmas
JZ Leibo, V Zambaldi, M Lanctot, J Marecki, T Graepel
arXiv preprint arXiv:1702.03037, 2017
2092017
A unified game-theoretic approach to multiagent reinforcement learning
M Lanctot, V Zambaldi, A Gruslys, A Lazaridou, K Tuyls, J Pérolat, D Silver, ...
Advances in Neural Information Processing Systems, 4190-4203, 2017
1412017
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
76*2018
Dawn of the selfie era: The whos, wheres, and hows of selfies on Instagram
F Souza, D de Las Casas, V Flores, SB Youn, M Cha, D Quercia, ...
Proceedings of the 2015 ACM on conference on online social networks, 221-231, 2015
692015
Value-decomposition networks for cooperative multi-agent learning
P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ...
arXiv preprint arXiv:1706.05296, 2017
582017
A multi-agent reinforcement learning model of common-pool resource appropriation
J Perolat, JZ Leibo, V Zambaldi, C Beattie, K Tuyls, T Graepel
Advances in Neural Information Processing Systems, 3643-3652, 2017
572017
Value-decomposition networks for cooperative multi-agent learning based on team reward
P Sunehag, G Lever, A Gruslys, WM Czarnecki, V Zambaldi, M Jaderberg, ...
Proceedings of the 17th international conference on autonomous agents and …, 2018
462018
Actor-critic policy optimization in partially observable multiagent environments
S Srinivasan, M Lanctot, V Zambaldi, J Pérolat, K Tuyls, R Munos, ...
Advances in neural information processing systems, 3422-3435, 2018
372018
Lightweight contextual ranking of city pictures: Urban sociology to the rescue
VF Zambaldi, JP Pesce, D Quercia, V Almeida
Eighth International AAAI Conference on Weblogs and Social Media, 2014
132014
Relational forward models for multi-agent learning
A Tacchetti, HF Song, PAM Mediano, V Zambaldi, NC Rabinowitz, ...
arXiv preprint arXiv:1809.11044, 2018
102018
Compile: Compositional imitation learning and execution
T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ...
arXiv preprint arXiv:1812.01483, 2018
52018
Openspiel: A framework for reinforcement learning in games
M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, J Pérolat, ...
arXiv preprint arXiv:1908.09453, 2019
42019
Compositional imitation learning: Explaining and executing one task at a time
T Kipf, Y Li, H Dai, V Zambaldi, E Grefenstette, P Kohli, P Battaglia
arXiv preprint arXiv:1812.01483, 2018
42018
Reinforcement learning using a relational network for generating data encoding relationships between entities in an environment
Y Li, VC Bapst, V Zambaldi, DN Raposo, AA Santoro
US Patent App. 16/417,580, 2019
2019
Deep Learning Monitor
CT Page, M Lanctot, E Lockhart, JB Lespiau, V Zambaldi, S Upadhyay, ...
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