Riashat Islam

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 41

Top Topics

Perceptual Aliasing

Continuous State And Action Spaces

Reinforcement Learning

Policy Gradient

Top Venues

Publications

Lili Wu, Ben Evans, Riashat Islam, Raihan Seraj, Yonathan Efroni, Alex Lamb
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs. CoRR (2024)
Ruixiang Sun, Hongyu Zang, Xin Li, Riashat Islam
Learning Latent Dynamic Robust Representations for World Models. CoRR (2024)
Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal
EQA-MX: Embodied Question Answering using Multimodal Expression. ICLR (2024)
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 (2024)
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 (2024)
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)
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)
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)
Anurag Koul, Shivakanth Sujit, Shaoru Chen, Ben Evans, Lili Wu, Byron Xu, Rajan Chari, Riashat Islam, Raihan Seraj, Yonathan Efroni, Lekan P. Molu, Miro Dudík, John Langford, Alex Lamb
PcLast: Discovering Plannable Continuous Latent States. CoRR (2023)
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)
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)
Manan Tomar, Riashat Islam, Sergey Levine, Philip Bachman
Ignorance is Bliss: Robust Control via Information Gating. CoRR (2023)
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. CoRR (2023)
Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman
Ignorance is Bliss: Robust Control via Information Gating. NeurIPS (2023)
Alex Lamb, Riashat Islam, Yonathan Efroni, Aniket Didolkar, Dipendra Misra, Dylan J. Foster, Lekan Molu, Rajan Chari, Akshay Krishnamurthy, John Langford
Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. CoRR (2022)
Riashat Islam, Manan Tomar, Alex Lamb, Yonathan Efroni, Hongyu Zang, Aniket Didolkar, Dipendra Misra, Xin Li, Harm van Seijen, Remi Tachet des Combes, John Langford
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. CoRR (2022)
Riashat Islam, Samarth Sinha, Homanga Bharadhwaj, Samin Yeasar Arnob, Zhuoran Yang, Animesh Garg, Zhaoran Wang, Lihong Li, Doina Precup
Offline Policy Optimization in RL with Variance Regularizaton. CoRR (2022)
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 (2022)
Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex M. 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)
Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet des Combes, Romain Laroche
Behavior Prior Representation learning for Offline Reinforcement Learning. CoRR (2022)
Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. CoRR (2022)
Samin Yeasar Arnob, Riashat Islam, Doina Precup
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning. CoRR (2021)
Riashat Islam, Zafarali Ahmed, Doina Precup
Marginalized State Distribution Entropy Regularization in Policy Optimization. CoRR (2019)
Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam
Transfer Learning by Modeling a Distribution over Policies. CoRR (2019)
Riashat Islam, Komal K. Teru, Deepak Sharma
Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift. CoRR (2019)
Riashat Islam, Raihan Seraj, Samin Yeasar Arnob, Doina Precup
Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning. CoRR (2019)
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Hugo Larochelle, Matthew Botvinick, Yoshua Bengio, Sergey Levine
InfoBot: Transfer and Exploration via the Information Bottleneck. ICLR (Poster) (2019)
Anirudh Goyal, Riashat Islam, Daniel Strouse, Zafarali Ahmed, Matthew Botvinick, Hugo Larochelle, Sergey Levine, Yoshua Bengio
InfoBot: Transfer and Exploration via the Information Bottleneck. CoRR (2019)
Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup
Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods. CoRR (2019)
Philip Bachman, Riashat Islam, Alessandro Sordoni, Zafarali Ahmed
VFunc: a Deep Generative Model for Functions. CoRR (2018)
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger
Deep Reinforcement Learning That Matters. AAAI (2018)
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) (2018)
Arash Tavakoli, Vitaly Levdik, Riashat Islam, Petar Kormushev
Prioritizing Starting States for Reinforcement Learning. CoRR (2018)
Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau
An Introduction to Deep Reinforcement Learning. CoRR (2018)
David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville
Bayesian Hypernetworks. CoRR (2017)
Bogdan Mazoure, Riashat Islam
Alpha-Divergences in Variational Dropout. CoRR (2017)
Yarin Gal, Riashat Islam, Zoubin Ghahramani
Deep Bayesian Active Learning with Image Data. CoRR (2017)
Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger
Deep Reinforcement Learning that Matters. CoRR (2017)
Yarin Gal, Riashat Islam, Zoubin Ghahramani
Deep Bayesian Active Learning with Image Data. ICML (2017)
Peter Henderson, Thang Doan, Riashat Islam, David Meger
Bayesian Policy Gradients via Alpha Divergence Dropout Inference. CoRR (2017)
Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup
Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. CoRR (2017)