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Bernardo Ávila Pires
Bernardo Ávila Pires
Research Scientist, DeepMind
Verified email at google.com
Title
Cited by
Cited by
Year
Bootstrap your own latent-a new approach to self-supervised learning
JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ...
Advances in neural information processing systems 33, 21271-21284, 2020
16172020
Bootstrap latent-predictive representations for multitask reinforcement learning
ZD Guo, BA Pires, B Piot, JB Grill, F Altché, R Munos, MG Azar
International Conference on Machine Learning, 3875-3886, 2020
652020
Neural predictive belief representations
ZD Guo, MG Azar, B Piot, BA Pires, R Munos
arXiv preprint arXiv:1811.06407, 2018
482018
Cost-sensitive multiclass classification risk bounds
BA Pires, C Szepesvari, M Ghavamzadeh
International Conference on Machine Learning, 1391-1399, 2013
472013
World discovery models
MG Azar, B Piot, BA Pires, JB Grill, F Altché, R Munos
arXiv preprint arXiv:1902.07685, 2019
272019
Statistical linear estimation with penalized estimators: an application to reinforcement learning
BA Pires, C Szepesvári
arXiv preprint arXiv:1206.6444, 2012
272012
Policy error bounds for model-based reinforcement learning with factored linear models
BÁ Pires, C Szepesvári
Conference on Learning Theory, 121-151, 2016
222016
Mine your own view: Self-supervised learning through across-sample prediction
M Azabou, MG Azar, R Liu, CH Lin, EC Johnson, K Bhaskaran-Nair, ...
arXiv preprint arXiv:2102.10106, 2021
172021
Pseudo-MDPs and factored linear action models
H Yao, C Szepesvári, BA Pires, X Zhang
2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement …, 2014
172014
Neural belief states for partially observed domains
P Moreno, J Humplik, G Papamakarios, BA Pires, L Buesing, N Heess, ...
NeurIPS 2018 workshop on reinforcement learning under partial observability, 2018
152018
Multiclass classification calibration functions
BÁ Pires, C Szepesvári
arXiv preprint arXiv:1609.06385, 2016
142016
Bootstrap your own latent: A new approach to self-supervised learning. arXiv 2020
JB Grill, F Strub, F Altché, C Tallec, PH Richemond, E Buchatskaya, ...
arXiv preprint arXiv:2006.07733, 0
13
Bootstrap your own latent: a new approach to self-supervised Learning 2020
JB Grill, F Strub, F Altché, C Tallec, PH Richemond, E Buchatskaya, ...
arXiv preprint arXiv:2006.07733, 2021
112021
Bootstrap your own latent: A new approach to self-supervised learning. arXiv
JB Grill, F Strub, F Altché, C Tallec, PH Richemond, E Buchatskaya, ...
arXiv preprint arXiv:2006.07733, 2020
102020
Geometric entropic exploration
ZD Guo, MG Azar, A Saade, S Thakoor, B Piot, BA Pires, M Valko, ...
arXiv preprint arXiv:2101.02055, 2021
82021
Neural recursive belief states in multi-agent reinforcement learning
P Moreno, E Hughes, KR McKee, BA Pires, T Weber
arXiv preprint arXiv:2102.02274, 2021
72021
Statistical analysis of l1-penalized linear estimation with applications
B Ávila Pires
62012
Clause Identification Using Entropy Guided Transformation Learning
ER Fernandes, B Pires, CN dos Santos, RL Milidiú
Information and Human Language Technology (STIL), 2009 Seventh Brazilian …, 2009
52009
k. kavukcuoglu, R. Munos, and M. Valko,“Bootstrap your own latent-a new approach to self-supervised learning,” vol. 33
JB Grill, F Strub, F Altché, C Tallec, P Richemond, E Buchatskaya, ...
22020
Pathological effects of variance on classification-based policy iteration
BÁ Pires, C Szepesvári
Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
12015
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Articles 1–20