Dopamine: A Research Framework for Deep Reinforcement Learning. - Pablo Samuel Castro; Subhodeep Moitra; Carles Gelada; Saurabh Kumar 004; Marc G. Bellemare (CoRR, 2018)

DeepMDP: Learning Continuous Latent Space Models for Representation Learning. - Carles Gelada; Saurabh Kumar 004; Jacob Buckman; Ofir Nachum; Marc G. Bellemare (ICML, 2019)

Statistics and Samples in Distributional Reinforcement Learning. - Mark Rowland 001; Robert Dadashi; Saurabh Kumar 004; Rémi Munos; Marc G. Bellemare; Will Dabney (ICML, 2019)

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL. - Saurabh Kumar 004; Aviral Kumar; Sergey Levine; Chelsea Finn (NeurIPS, 2020)

Gradient Surgery for Multi-Task Learning. - Tianhe Yu; Saurabh Kumar 004; Abhishek Gupta 004; Sergey Levine; Karol Hausman; Chelsea Finn (NeurIPS, 2020)

Characterizing the Gap Between Actor-Critic and Policy Gradient. - Junfeng Wen; Saurabh Kumar 004; Ramki Gummadi; Dale Schuurmans (ICML, 2021)

A Parametric Class of Approximate Gradient Updates for Policy Optimization. - Ramki Gummadi; Saurabh Kumar 004; Junfeng Wen; Dale Schuurmans (ICML, 2022)

Maintaining Plasticity via Regenerative Regularization. - Saurabh Kumar 004; Henrik Marklund; Benjamin Van Roy (CoRR, 2023)

Maintaining Plasticity in Continual Learning via Regenerative Regularization. - Saurabh Kumar 004; Henrik Marklund; Benjamin Van Roy (CoLLAs, 2024)

Learning Continually by Spectral Regularization. - Alex Lewandowski; Saurabh Kumar 004; Dale Schuurmans; András György 001; Marlos C. Machado (CoRR, 2024)

Satisficing Exploration for Deep Reinforcement Learning. - Dilip Arumugam; Saurabh Kumar 004; Ramki Gummadi; Benjamin Van Roy (CoRR, 2024)

The Need for a Big World Simulator: A Scientific Challenge for Continual Learning. - Saurabh Kumar 004; Hong Jun Jeon; Alex Lewandowski; Benjamin Van Roy (CoRR, 2024)

Learning Continually by Spectral Regularization. - Alex Lewandowski; Michal Bortkiewicz; Saurabh Kumar 004; András György 001; Dale Schuurmans; Mateusz Ostaszewski; Marlos C. Machado (ICLR, 2025)

Continual Learning as Computationally Constrained Reinforcement Learning. - Saurabh Kumar 004; Henrik Marklund; Ashish Rao; Yifan Zhu; Hong Jun Jeon; Yueyang Liu; Benjamin Van Roy (Found. Trends Mach. Learn., 2025)

Conformal Transformations for Symmetric Power Transformers. - Saurabh Kumar 004; Jacob Buckman; Carles Gelada; Sean Zhang (CoRR, 2025)