Riashat Islam

According to our database, Riashat Islam authored at least 34 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

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

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, Avishek Joey Bose

CoRR, 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

Learning Latent Dynamic Robust Representations for World Models.

Ruixiang Sun, Hongyu Zang, Xin Li, Riashat Islam

Proceedings of the Forty-first International Conference on Machine Learning, 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, John Langford, Alex Lamb

Proceedings of the Forty-first International Conference on Machine Learning, 2024

EQA-MX: Embodied Question Answering using Multimodal Expression.

Md Mofijul Islam, Alexi Gladstone, Riashat Islam, Tariq Iqbal

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Trans. Mach. Learn. Res., 2023

Ignorance is Bliss: Robust Control via Information Gating.

Manan Tomar, Riashat Islam, Sergey Levine, Philip Bachman

CoRR, 2023

Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning.

Hongyu Zang, Xin Li, Leiji Zhang, Yang Liu, Baigui Sun, Riashat Islam, Remi Tachet des Combes, Romain Laroche

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Ignorance is Bliss: Robust Control via Information Gating.

Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine, Philip Bachman

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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, Harm van Seijen, Remi Tachet des Combes, John Langford

Proceedings of the International Conference on Machine Learning, 2023

Behavior Prior Representation learning for Offline Reinforcement Learning.

Hongyu Zang, Xin Li, Jie Yu, Chen Liu, Riashat Islam, Remi Tachet des Combes, Romain Laroche

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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, Anirudh Goyal, Nicolas Heess, Alex Lamb

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Offline Policy Optimization in RL with Variance Regularizaton.

Riashat Islam, Samarth Sinha, Homanga Bharadhwaj, Samin Yeasar Arnob, Zhuoran Yang, Animesh Garg, Zhaoran Wang, Lihong Li, Doina Precup

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, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes

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, Harm van Seijen, Remi Tachet des Combes, John Langford

CoRR, 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

CoRR, 2022

Discrete Compositional Representations as an Abstraction for Goal Conditioned Reinforcement Learning.

Riashat Islam, Hongyu Zang, Anirudh Goyal, Alex Lamb, Kenji Kawaguchi, Xin Li, Romain Laroche, Yoshua Bengio, Remi Tachet des Combes

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning.

Samin Yeasar Arnob, Riashat Islam, Doina Precup

CoRR, 2021

2019

Marginalized State Distribution Entropy Regularization in Policy Optimization.

Riashat Islam, Zafarali Ahmed, 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

Entropy Regularization with Discounted Future State Distribution in Policy Gradient Methods.

Riashat Islam, Raihan Seraj, Pierre-Luc Bacon, Doina Precup

CoRR, 2019

Off-Policy Policy Gradient Algorithms by Constraining the State Distribution Shift.

Riashat Islam, Komal K. Teru, Deepak Sharma

CoRR, 2019

Transfer Learning by Modeling a Distribution over Policies.

Disha Shrivastava, Eeshan Gunesh Dhekane, Riashat Islam

CoRR, 2019

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

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

An Introduction to Deep Reinforcement Learning.

Vincent François-Lavet, Peter Henderson, Riashat Islam, Marc G. Bellemare, Joelle Pineau

Found. Trends Mach. Learn., 2018

Prioritizing Starting States for Reinforcement Learning.

Arash Tavakoli, Vitaly Levdik, Riashat Islam, Petar Kormushev

CoRR, 2018

VFunc: a Deep Generative Model for Functions.

Philip Bachman, Riashat Islam, Alessandro Sordoni, Zafarali Ahmed

CoRR, 2018

Deep Reinforcement Learning That Matters.

Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Bayesian Policy Gradients via Alpha Divergence Dropout Inference.

Peter Henderson, Thang Doan, Riashat Islam, David Meger

CoRR, 2017

Alpha-Divergences in Variational Dropout.

Bogdan Mazoure, Riashat Islam

CoRR, 2017

Bayesian Hypernetworks.

David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron C. Courville

CoRR, 2017

Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control.

Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup

CoRR, 2017

Deep Bayesian Active Learning with Image Data.

Yarin Gal, Riashat Islam, Zoubin Ghahramani

Proceedings of the 34th International Conference on Machine Learning, 2017