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Manfred Diaz
Manfred Diaz
Ph.D. Student, Mila / University of Montreal
在 iro.umontreal.ca 的电子邮件经过验证 - 首页
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引用次数
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年份
Active domain randomization
B Mehta, M Diaz, F Golemo, CJ Pal, L Paull
Conference on Robot Learning, 1162-1176, 2020
2962020
The ai driving olympics at neurips 2018
J Zilly, J Tani, B Considine, B Mehta, AF Daniele, M Diaz, G Bernasconi, ...
The NeurIPS'18 Competition: From Machine Learning to Intelligent …, 2020
192020
Braxlines: Fast and interactive toolkit for rl-driven behavior engineering beyond reward maximization
SS Gu, M Diaz, DC Freeman, H Furuta, SKS Ghasemipour, A Raichuk, ...
arXiv preprint arXiv:2110.04686, 2021
162021
To Veer or Not to Veer: Learning From Experts How to Stay Within the Crosswalk
M Diaz, R Girgis, T Fevens, J Cooperstock
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017
112017
A theory of appropriateness with applications to generative artificial intelligence
JZ Leibo, AS Vezhnevets, M Diaz, JP Agapiou, WA Cunningham, ...
arXiv preprint arXiv:2412.19010, 2024
22024
Generalization Games for Reinforcement Learning
M Diaz, C Gauthier, G Berseth, L Paull
ICLR 2022 Workshop on Gamification and Multiagent Solutions, 2022
22022
Uncertainty-Aware Policy Sampling and Mixing for Safe Interactive Imitation Learning
M Diaz, T Fevens, L Paull
2021 18th Conference on Robots and Vision (CRV), 72-78, 2021
22021
Interactive and Uncertainty-aware Imitation Learning: Theory and Applications
MR Diaz Cabrera
Concordia University, 2018
12018
Soft Condorcet Optimization for Ranking of General Agents
M Lanctot, K Larson, M Kaisers, Q Berthet, I Gemp, M Diaz, ...
arXiv preprint arXiv:2411.00119, 2024
2024
Rethinking Teacher-Student Curriculum Learning through the Cooperative Mechanics of Experience
M Diaz, L Paull, A Tacchetti
arXiv preprint arXiv:2404.03084, 2024
2024
Milnor-Myerson Games and The Principles of Artificial Principal-Agent Problems
M Diaz, JZ Leibo, L Paull
Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks, 2024
2024
LOCO: Adaptive exploration in reinforcement learning via local estimation of contraction coefficients
M Diaz, L Paull, PS Castro
ICLR 2021 Workshop on Self-supervision for Reinforcement Learning (SSL-RL), 2021
2021
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