Követés
Riashat Islam
Riashat Islam
Research Scientist
E-mail megerősítve itt: mail.mcgill.ca - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Deep reinforcement learning that matters
P Henderson*, R Islam*, P Bachman, J Pineau, D Precup, D Meger
Proceedings of 32nd AAAI Conference on Artificial Intelligence (AAAI-18), 2017
25982017
Deep Bayesian Active Learning with Image Data
Y Gal, R Islam, Z Ghahramani
Proceedings of the 34th International Conference on Machine Learning (ICML-17), 2017
21032017
An introduction to deep reinforcement learning
V François-Lavet, P Henderson, R Islam, MG Bellemare, J Pineau
Foundations and Trends® in Machine Learning 11 (3-4), 219-354, 2018
19602018
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control
R Islam, P Henderson, M Gomrokchi, D Precup
Reproducibility in Machine Learning Workshop, ICML 2017, 2017
3422017
Bayesian Hypernetworks
D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville
arXiv preprint arXiv:1710.04759, 2017
1932017
InfoBot : Transfer and Exploration via the Information Bottleneck
A Goyal, R Islam, DJ Strouse, Z Ahmed, H Larochelle, M Botvinick, ...
International Conference on Learning Representations (ICLR) 2019, 2018
1812018
Guaranteed discovery of controllable latent states with multi-step inverse models
A Lamb, R Islam, Y Efroni, A Didolkar, D Misra, D Foster, L Molu, R Chari, ...
arXiv preprint arXiv:2207.08229, 2022
242022
Re-evaluate: Reproducibility in evaluating reinforcement learning algorithms
K Khetarpal, Z Ahmed, A Cianflone, R Islam, J Pineau
232018
Marginalized state distribution entropy regularization in policy optimization
R Islam, Z Ahmed, D Precup
arXiv preprint arXiv:1912.05128, 2019
192019
Bayesian Policy Gradients via Alpha Divergence Dropout Inference
P Henderson, T Doan, R Islam, D Meger
Bayesian Deep Learning Workshop, NIPS 2017, 2017
192017
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
R Islam, H Zang, A Goyal, A Lamb, K Kawaguchi, X Li, R Laroche, ...
NeurIPS 2022, 2022
162022
Agent-controller representations: Principled offline rl with rich exogenous information
R Islam, M Tomar, A Lamb, Y Efroni, H Zang, A Didolkar, D Misra, X Li, ...
ICML 2023; arXiv:2211.00164, 2023
152023
Guaranteed discovery of control-endogenous latent states with multi-step inverse models
A Lamb, R Islam, Y Efroni, A Didolkar, D Misra, D Foster, L Molu, R Chari, ...
arXiv preprint arXiv:2207.08229, 2022
152022
Active Learning for High Dimensional Inputs using Bayesian Convolutional Neural Networks
R Islam, Y Gal, Z Ghahramani
University of Cambridge, Masters Thesis, 2016
142016
Sequence-Augmented SE (3)-Flow Matching For Conditional Protein Backbone Generation
G Huguet, J Vuckovic, K Fatras, E Thibodeau-Laufer, P Lemos, R Islam, ...
arXiv preprint arXiv:2405.20313, 2024
132024
Variational state encoding as intrinsic motivation in reinforcement learning
M Klissarov, R Islam, K Khetarpal, D Precup
Task-Agnostic Reinforcement Learning Workshop at Proceedings of the …, 2019
132019
Exploring restart distributions
A Tavakoli, V Levdik, R Islam, CM Smith, P Kormushev
arXiv preprint arXiv:1811.11298, 2018
132018
Entropy regularization with discounted future state distribution in policy gradient methods
R Islam, R Seraj, PL Bacon, D Precup
arXiv preprint arXiv:1912.05104, 2019
112019
Behavior prior representation learning for offline reinforcement learning
H Zang, X Li, J Yu, C Liu, R Islam, RTD Combes, R Laroche
arXiv preprint arXiv:2211.00863, 2022
102022
Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift
R Islam, KK Teru, D Sharma, J Pineau
https://arxiv.org/abs/1911.06970, 2019
102019
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