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Riashat Islam
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Journal Articles
- 2023
- [j2]Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Rajiv Didolkar, Dipendra Misra, Dylan J. Foster, Lekan P. Molu, Rajan Chari, Akshay Krishnamurthy, John Langford:
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. Trans. Mach. Learn. Res. 2023 (2023) - 2018
- [j1]Vincent François-Lavet, Peter Henderson, Riashat Islam
, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. Found. Trends Mach. Learn. 11(3-4): 219-354 (2018)
Conference and Workshop Papers
- 2024
- [c12]Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal:
EQA-MX: Embodied Question Answering using Multimodal Expression. ICLR 2024 - [c11]Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miroslav Dudík, John Langford, Alex Lamb:
PcLast: Discovering Plannable Continuous Latent States. ICML 2024 - [c10]Ruixiang Sun, Hongyu Zang, Xin Li, Riashat Islam:
Learning Latent Dynamic Robust Representations for World Models. ICML 2024 - 2023
- [c9]Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb:
Representation Learning in Deep RL via Discrete Information Bottleneck. AISTATS 2023: 8699-8722 - [c8]Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet des Combes, Romain Laroche:
Behavior Prior Representation learning for Offline Reinforcement Learning. ICLR 2023 - [c7]Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Rajiv Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford:
Principled Offline RL in the Presence of Rich Exogenous Information. ICML 2023: 14390-14421 - [c6]Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman:
Ignorance is Bliss: Robust Control via Information Gating. NeurIPS 2023 - [c5]Hongyu Zang, Xin Li, Leiji Zhang, Yang Liu, Baigui Sun, Riashat Islam, Remi Tachet des Combes, Romain Laroche:
Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning. NeurIPS 2023 - 2022
- [c4]Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes:
Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. NeurIPS 2022 - 2019
- [c3]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew M. Botvinick, Yoshua Bengio, Sergey Levine:
InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) 2019 - 2018
- [c2]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning That Matters. AAAI 2018: 3207-3214 - 2017
- [c1]Yarin Gal, Riashat Islam, Zoubin Ghahramani:
Deep Bayesian Active Learning with Image Data. ICML 2017: 1183-1192
Informal and Other Publications
- 2024
- [i29]Lili Wu, Ben Evans, Riashat Islam
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs. CoRR abs/2404.14552 (2024) - [i28]Ruixiang Sun, Hongyu Zang, Xin Li, Riashat Islam
Learning Latent Dynamic Robust Representations for World Models. CoRR abs/2405.06263 (2024) - [i27]Guillaume Huguet, James Vuckovic, Kilian Fatras, Eric Thibodeau-Laufer, Pablo Lemos, Riashat Islam, Cheng-Hao Liu, Jarrid Rector-Brooks, Tara Akhound-Sadegh, Michael M. Bronstein, Alexander Tong, Avishek Joey Bose:
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. CoRR abs/2405.20313 (2024) - [i26]Jithendaraa Subramanian, Shivakanth Sujit, Niloy Irtisam, Umong Sain, Derek Nowrouzezahrai, Samira Ebrahimi Kahou, Riashat Islam:
Reinforcement Learning for Sequence Design Leveraging Protein Language Models. CoRR abs/2407.03154 (2024) - 2023
- [i25]Manan Tomar, Riashat Islam
Ignorance is Bliss: Robust Control via Information Gating. CoRR abs/2303.06121 (2023) - [i24]Hongyu Zang, Xin Li, Leiji Zhang, Yang Liu, Baigui Sun, Riashat Islam
Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning. CoRR abs/2310.17139 (2023) - [i23]Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam
PcLast: Discovering Plannable Continuous Latent States. CoRR abs/2311.03534 (2023) - 2022
- [i22]Alex Lamb, Riashat Islam
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR abs/2207.08229 (2022) - [i21]Riashat Islam
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. CoRR abs/2211.00164 (2022) - [i20]Riashat Islam
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR abs/2211.00247 (2022) - [i19]Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam
Behavior Prior Representation learning for Offline Reinforcement Learning. CoRR abs/2211.00863 (2022) - [i18]Riashat Islam, Hongyu Zang, Manan Tomar, Aniket Didolkar, Md Mofijul Islam, Samin Yeasar Arnob, Tariq Iqbal, Xin Li, Anirudh Goyal, Nicolas Heess, Alex Lamb:
Representation Learning in Deep RL via Discrete Information Bottleneck. CoRR abs/2212.13835 (2022) - [i17]Riashat Islam
Offline Policy Optimization in RL with Variance Regularizaton. CoRR abs/2212.14405 (2022) - 2021
- [i16]Samin Yeasar Arnob, Riashat Islam, Doina Precup:
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning. CoRR abs/2112.15578 (2021) - 2019
- [i15]Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew M. Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio:
InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR abs/1901.10902 (2019) - [i14]Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam:
Transfer Learning by Modeling a Distribution over Policies. CoRR abs/1906.03574 (2019) - [i13]Riashat Islam, Komal K. Teru, Deepak Sharma:
Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift. CoRR abs/1911.06970 (2019) - [i12]Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup:
Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods. CoRR abs/1912.05104 (2019) - [i11]Riashat Islam, Raihan Seraj, Samin Yeasar Arnob, Doina Precup:
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning. CoRR abs/1912.05109 (2019) - [i10]Riashat Islam, Zafarali Ahmed, Doina Precup:
Marginalized State Distribution Entropy Regularization in Policy Optimization. CoRR abs/1912.05128 (2019) - 2018
- [i9]Philip Bachman, Riashat Islam, Alessandro Sordoni, Zafarali Ahmed:
VFunc: a Deep Generative Model for Functions. CoRR abs/1807.04106 (2018) - [i8]Arash Tavakoli, Vitaly Levdik, Riashat Islam, Petar Kormushev:
Prioritizing Starting States for Reinforcement Learning. CoRR abs/1811.11298 (2018) - [i7]Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau:
An Introduction to Deep Reinforcement Learning. CoRR abs/1811.12560 (2018) - 2017
- [i6]Yarin Gal, Riashat Islam, Zoubin Ghahramani:
Deep Bayesian Active Learning with Image Data. CoRR abs/1703.02910 (2017) - [i5]Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup:
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR abs/1708.04133 (2017) - [i4]Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger:
Deep Reinforcement Learning that Matters. CoRR abs/1709.06560 (2017) - [i3]David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville:
Bayesian Hypernetworks. CoRR abs/1710.04759 (2017) - [i2]Bogdan Mazoure, Riashat Islam:
Alpha-Divergences in Variational Dropout. CoRR abs/1711.04345 (2017) - [i1]Peter Henderson, Thang Doan, Riashat Islam, David Meger:
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR abs/1712.02037 (2017)
Coauthor Index
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