Riashat Islam

Computer Science · Physical Sciences

13h-index5.0kcitations45works0.82yr avg
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Research Topics

Reinforcement Learning in Robotics(25), Advanced Bandit Algorithms Research(8), Smart Grid Energy Management(7), Machine Learning and Data Classification(6), Adversarial Robustness in Machine Learning(4)

Publications45 total

Next-Latent Prediction Transformers Learn Compact World Models
arXiv (Cornell University)·2025Open Access
h1: Bootstrapping LLMs to Reason over Longer Horizons via Reinforcement Learning
arXiv (Cornell University)·2025Open Access
Wavelet Predictive Representations for Non-Stationary Reinforcement Learning
arXiv (Cornell University)·2025Open Access
Learning Fused State Representations for Control from Multi-View Observations
arXiv (Cornell University)·2025Open Access
Reinforcement Learning for Sequence Design Leveraging Protein Language Models
arXiv (Cornell University)·2024Open Access
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation
arXiv (Cornell University)·2024· 6 citedOpen Access
Learning Latent Dynamic Robust Representations for World Models
arXiv (Cornell University)·2024Open Access
Generalizing Multi-Step Inverse Models for Representation Learning to Finite-Memory POMDPs
arXiv (Cornell University)·2024Open Access
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Generation
2024· 1 cited
PcLast: Discovering Plannable Continuous Latent States
arXiv (Cornell University)·2023Open Access
Understanding and Addressing the Pitfalls of Bisimulation-based Representations in Offline Reinforcement Learning
arXiv (Cornell University)·2023· 1 citedOpen Access
Ignorance is Bliss: Robust Control via Information Gating
arXiv (Cornell University)·2023Open Access
Offline Policy Optimization in RL with Variance Regularizaton
arXiv (Cornell University)·2022Open Access
Representation Learning in Deep RL via Discrete Information Bottleneck
arXiv (Cornell University)·2022· 1 citedOpen Access
Behavior Prior Representation learning for Offline Reinforcement Learning
arXiv (Cornell University)·2022· 3 citedOpen Access
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
arXiv (Cornell University)·2022· 4 citedOpen Access
Agent-Controller Representations: Principled Offline RL with Rich Exogenous Information
arXiv (Cornell University)·2022Open Access
Guaranteed Discovery of Control-Endogenous Latent States with Multi-Step Inverse Models
arXiv (Cornell University)·2022· 1 citedOpen Access
Importance of Empirical Sample Complexity Analysis for Offline Reinforcement Learning
arXiv (Cornell University)·2021· 3 citedOpen Access
Offline Policy Optimization with Variance Regularization
2021
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Frequent Co-authors

Doina Precup(10), Hongyu Zang(7), Alex Lamb(7), Peter Henderson(6), Joëlle Pineau(6), Zafarali Ahmed(6), Xin Li(6), Samin Yeasar Arnob(6), Anirudh Goyal(5), Raihan Seraj(5), Philip Bachman(4), Yoshua Bengio(4), Sergey Levine(4), Romain Laroche(4), Rémi Tachet des Combes(4), Yonathan Efroni(4), John Langford(4), Manan Tomar(4), David Meger(3), Daniel Strouse(3)