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Alexandre Galashov
Alexandre Galashov
DeepMind
Email verificata su google.com
Titolo
Citata da
Citata da
Anno
Neural probabilistic motor primitives for humanoid control
J Merel, L Hasenclever, A Galashov, A Ahuja, V Pham, G Wayne, YW Teh, ...
arXiv preprint arXiv:1811.11711, 2018
1302018
Meta reinforcement learning as task inference
J Humplik, A Galashov, L Hasenclever, PA Ortega, YW Teh, N Heess
arXiv preprint arXiv:1905.06424, 2019
1202019
Task agnostic continual learning via meta learning
X He, J Sygnowski, A Galashov, AA Rusu, YW Teh, R Pascanu
arXiv preprint arXiv:1906.05201, 2019
1062019
Information asymmetry in KL-regularized RL
A Galashov, SM Jayakumar, L Hasenclever, D Tirumala, J Schwarz, ...
arXiv preprint arXiv:1905.01240, 2019
932019
Information asymmetry in KL-regularized RL
A Galashov, SM Jayakumar, L Hasenclever, D Tirumala, J Schwarz, ...
arXiv preprint arXiv:1905.01240, 2019
932019
Game Plan: What AI can do for Football, and What Football can do for AI
K Tuyls, S Omidshafiei, P Muller, Z Wang, J Connor, D Hennes, I Graham, ...
Journal of Artificial Intelligence Research 71, 41-88, 2021
722021
Exploiting hierarchy for learning and transfer in kl-regularized rl
D Tirumala, H Noh, A Galashov, L Hasenclever, A Ahuja, G Wayne, ...
arXiv preprint arXiv:1903.07438, 2019
412019
Learning dexterous manipulation from suboptimal experts
R Jeong, JT Springenberg, J Kay, D Zheng, Y Zhou, A Galashov, N Heess, ...
arXiv preprint arXiv:2010.08587, 2020
312020
Behavior priors for efficient reinforcement learning
D Tirumala, A Galashov, H Noh, L Hasenclever, R Pascanu, J Schwarz, ...
The Journal of Machine Learning Research 23 (1), 9989-10056, 2022
292022
Meta-learning surrogate models for sequential decision making
A Galashov, J Schwarz, H Kim, M Garnelo, D Saxton, P Kohli, SM Eslami, ...
arXiv preprint arXiv:1903.11907, 2019
262019
A 2-approximate algorithm to solve one problem of the family of disjoint vector subsets
AE Galashov, AV Kel’manov
Automation and Remote Control 75, 595-606, 2014
152014
Temporal difference uncertainties as a signal for exploration
S Flennerhag, JX Wang, P Sprechmann, F Visin, A Galashov, ...
arXiv preprint arXiv:2010.02255, 2020
132020
Information theoretic meta learning with gaussian processes
MK Titsias, FJR Ruiz, S Nikoloutsopoulos, A Galashov
Uncertainty in Artificial Intelligence, 1597-1606, 2021
112021
Nevis' 22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
J Bornschein, A Galashov, R Hemsley, A Rannen-Triki, Y Chen, ...
Journal of Machine Learning Research 24 (308), 1-77, 2023
72023
Data augmentation for efficient learning from parametric experts
A Galashov, JS Merel, N Heess
Advances in Neural Information Processing Systems 35, 31484-31496, 2022
42022
Learning motor primitives and training a machine learning system using a linear-feedback-stabilized policy
L Hasenclever, V Pham, J Merel, A Galashov
US Patent 11,403,513, 2022
42022
Importance Weighted Policy Learning and Adaptation
A Galashov, J Sygnowski, G Desjardins, J Humplik, L Hasenclever, ...
arXiv preprint arXiv:2009.04875, 2020
42020
Transferring task goals via hierarchical reinforcement learning
S Xie, A Galashov, S Liu, S Hou, R Pascanu, N Heess, YW Teh
22018
Kalman Filter for Online Classification of Non-Stationary Data
MK Titsias, A Galashov, A Rannen-Triki, R Pascanu, YW Teh, ...
arXiv preprint arXiv:2306.08448, 2023
12023
Towards Compute-Optimal Transfer Learning
M Caccia, A Galashov, A Douillard, A Rannen-Triki, D Rao, M Paganini, ...
arXiv preprint arXiv:2304.13164, 2023
12023
Il sistema al momento non pu eseguire l'operazione. Riprova pi tardi.
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