Deep Bayesian Active Learning with Image Data. - Yarin Gal; Riashat Islam; Zoubin Ghahramani (ICML, 2017)

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control. - Riashat Islam; Peter Henderson 002; Maziar Gomrokchi; Doina Precup (CoRR, 2017)

Bayesian Hypernetworks. - David Krueger 001; Chin-Wei Huang; Riashat Islam; Ryan Turner; Alexandre Lacoste; Aaron C. Courville (CoRR, 2017)

Alpha-Divergences in Variational Dropout. - Bogdan Mazoure; Riashat Islam (CoRR, 2017)

Bayesian Policy Gradients via Alpha Divergence Dropout Inference. - Peter Henderson 002; Thang Doan; Riashat Islam; David Meger (CoRR, 2017)

Deep Reinforcement Learning That Matters. - Peter Henderson 002; Riashat Islam; Philip Bachman; Joelle Pineau; Doina Precup; David Meger (AAAI, 2018)

VFunc: a Deep Generative Model for Functions. - Philip Bachman; Riashat Islam; Alessandro Sordoni; Zafarali Ahmed (CoRR, 2018)

Prioritizing Starting States for Reinforcement Learning. - Arash Tavakoli; Vitaly Levdik; Riashat Islam; Petar Kormushev (CoRR, 2018)

An Introduction to Deep Reinforcement Learning. - Vincent François-Lavet; Peter Henderson 002; Riashat Islam; Marc G. Bellemare; Joelle Pineau (Found. Trends Mach. Learn., 2018)

InfoBot: Transfer and Exploration via the Information Bottleneck. - Anirudh Goyal; Riashat Islam; Daniel Strouse; Zafarali Ahmed; Hugo Larochelle; Matthew M. Botvinick; Yoshua Bengio; Sergey Levine (ICLR (Poster), 2019)

Transfer Learning by Modeling a Distribution over Policies. - Disha Shrivastava; Eeshan Gunesh Dhekane; Riashat Islam (CoRR, 2019)

Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift. - Riashat Islam; Komal K. Teru; Deepak Sharma (CoRR, 2019)

Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods. - Riashat Islam; Raihan Seraj; Pierre-Luc Bacon; Doina Precup (CoRR, 2019)

Doubly Robust Off-Policy Actor-Critic Algorithms for Reinforcement Learning. - Riashat Islam; Raihan Seraj; Samin Yeasar Arnob; Doina Precup (CoRR, 2019)

Marginalized State Distribution Entropy Regularization in Policy Optimization. - Riashat Islam; Zafarali Ahmed; Doina Precup (CoRR, 2019)

Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning. - Samin Yeasar Arnob; Riashat Islam; Doina Precup (CoRR, 2021)

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (NeurIPS, 2022)

Guaranteed Discovery of Controllable Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (CoRR, 2022)

Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (CoRR, 2022)

Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning. - Riashat Islam; Hongyu Zang; Anirudh Goyal; Alex Lamb; Kenji Kawaguchi; Xin Li 033; Romain Laroche; Yoshua Bengio; Remi Tachet des Combes (CoRR, 2022)

Offline Policy Optimization in RL with Variance Regularizaton. - Riashat Islam; Samarth Sinha; Homanga Bharadhwaj; Samin Yeasar Arnob; Zhuoran Yang; Animesh Garg; Zhaoran Wang 001; Lihong Li; Doina Precup (CoRR, 2022)

Representation Learning in Deep RL via Discrete Information Bottleneck. - Riashat Islam; Hongyu Zang; Manan Tomar; Aniket Didolkar; Md Mofijul Islam; Samin Yeasar Arnob; Tariq Iqbal; Xin Li 033; Anirudh Goyal; Nicolas Heess; Alex Lamb (AISTATS, 2023)

Behavior Prior Representation learning for Offline Reinforcement Learning. - Hongyu Zang; Xin Li 033; Jie Yu; Chen Liu; Riashat Islam; Remi Tachet des Combes; Romain Laroche (ICLR, 2023)

Principled Offline RL in the Presence of Rich Exogenous Information. - Riashat Islam; Manan Tomar; Alex Lamb; Yonathan Efroni; Hongyu Zang; Aniket Rajiv Didolkar; Dipendra Misra; Xin Li 033; Harm van Seijen; Remi Tachet des Combes; John Langford 001 (ICML, 2023)

Ignorance is Bliss: Robust Control via Information Gating. - Manan Tomar; Riashat Islam; Matthew E. Taylor; Sergey Levine; Philip Bachman (NeurIPS, 2023)

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning. - Hongyu Zang; Xin Li 033; Leiji Zhang; Yang Liu 356; Baigui Sun; Riashat Islam; Remi Tachet des Combes; Romain Laroche (NeurIPS, 2023)

Ignorance is Bliss: Robust Control via Information Gating. - Manan Tomar; Riashat Islam; Sergey Levine; Philip Bachman (CoRR, 2023)

Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models. - Alex Lamb; Riashat Islam; Yonathan Efroni; Aniket Rajiv Didolkar; Dipendra Misra; Dylan J. Foster; Lekan P. Molu; Rajan Chari; Akshay Krishnamurthy; John Langford 001 (Trans. Mach. Learn. Res., 2023)

EQA-MX: Embodied Question Answering using Multimodal Expression. - Md Mofijul Islam; Alexi Gladstone; Riashat Islam; Tariq Iqbal (ICLR, 2024)

PcLast: Discovering Plannable Continuous Latent States. - 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; et al. (ICML, 2024)

Learning Latent Dynamic Robust Representations for World Models. - Ruixiang Sun 003; Hongyu Zang; Xin Li 033; Riashat Islam (ICML, 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation. - 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 001; Avishek Joey Bose (NeurIPS, 2024)

Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs. - Lili Wu; Ben Evans; Riashat Islam; Raihan Seraj; Yonathan Efroni; Alex Lamb (CoRR, 2024)

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation. - 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 001; Avishek Joey Bose (CoRR, 2024)

Reinforcement Learning for Sequence Design Leveraging Protein Language Models. - Jithendaraa Subramanian; Shivakanth Sujit; Niloy Irtisam; Umong Sain; Derek Nowrouzezahrai; Samira Ebrahimi Kahou; Riashat Islam (CoRR, 2024)

Learning Fused State Representations for Control from Multi-View Observations. - Zeyu Wang; Yao-Hui Li; Xin Li 033; Hongyu Zang; Romain Laroche; Riashat Islam (CoRR, 2025)