Vinicius Zambaldi
Vinicius Zambaldi
Google Deepmind
google.com üzerinde doğrulanmış e-posta adresine sahip
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
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
14752018
Multi-agent reinforcement learning in sequential social dilemmas
JZ Leibo, V Zambaldi, M Lanctot, J Marecki, T Graepel
arXiv preprint arXiv:1702.03037, 2017
4152017
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
4082017
A unified game-theoretic approach to multiagent reinforcement learning
M Lanctot, V Zambaldi, A Gruslys, A Lazaridou, K Tuyls, J Pérolat, D Silver, ...
arXiv preprint arXiv:1711.00832, 2017
3532017
Deep reinforcement learning with relational inductive biases
V Zambaldi, D Raposo, A Santoro, V Bapst, Y Li, I Babuschkin, K Tuyls, ...
International Conference on Learning Representations, 2018
262*2018
A multi-agent reinforcement learning model of common-pool resource appropriation
J Perolat, JZ Leibo, V Zambaldi, C Beattie, K Tuyls, T Graepel
arXiv preprint arXiv:1707.06600, 2017
1202017
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
1022015
Actor-critic policy optimization in partially observable multiagent environments
S Srinivasan, M Lanctot, V Zambaldi, J Pérolat, K Tuyls, R Munos, ...
arXiv preprint arXiv:1810.09026, 2018
922018
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
622019
Relational forward models for multi-agent learning
A Tacchetti, HF Song, PAM Mediano, V Zambaldi, NC Rabinowitz, ...
arXiv preprint arXiv:1809.11044, 2018
422018
Compile: Compositional imitation learning and execution
T Kipf, Y Li, H Dai, V Zambaldi, A Sanchez-Gonzalez, E Grefenstette, ...
International Conference on Machine Learning, 3418-3428, 2019
322019
Memo: A deep network for flexible combination of episodic memories
A Banino, AP Badia, R Köster, MJ Chadwick, V Zambaldi, D Hassabis, ...
arXiv preprint arXiv:2001.10913, 2020
152020
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
132018
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
The advantage regret-matching actor-critic
A Gruslys, M Lanctot, R Munos, F Timbers, M Schmid, J Perolat, D Morrill, ...
arXiv preprint arXiv:2008.12234, 2020
52020
The Spatial Memory Pipeline: a model of egocentric to allocentric understanding in mammalian brains
B Uria, B Ibarz, A Banino, V Zambaldi, D Kumaran, D Hassabis, C Barry, ...
bioRxiv, 2020
32020
Graph neural network systems for behavior prediction and reinforcement learning in multple agent environments
H Song, A Tacchetti, PW Battaglia, V Zambaldi
US Patent App. 17/054,632, 2021
2021
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
Relational inductive biases, deep learning, and graph networks (关系归纳偏差, 深度学习和图形网络)
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
Relational inductive biases, deep learning, and graph networks (關係歸納偏差, 深度學習和圖形網絡)
PW Battaglia, JB Hamrick, V Bapst, A Sanchez-Gonzalez, V Zambaldi, ...
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Makaleler 1–20