Off-policy Learning with Options and Recognizers. - Doina Precup; Richard S. Sutton; Cosmin Paduraru; Anna Koop; Satinder Singh 001 (NIPS, 2005)

Grounding Abstractions in Predictive State Representations. - Brian Tanner; Vadim Bulitko; Anna Koop; Cosmin Paduraru (IJCAI, 2007)

A Framework for Computing Bounds for the Return of a Policy. - Cosmin Paduraru; Doina Precup; Joelle Pineau (EWRL, 2011)

An Empirical Analysis of Off-policy Learning in Discrete MDPs. - Cosmin Paduraru; Doina Precup; Joelle Pineau; Gheorghe Comanici (EWRL, 2012)

Safe Exploration in Continuous Action Spaces. - Gal Dalal; Krishnamurthy Dvijotham; Matej Vecerík; Todd Hester; Cosmin Paduraru; Yuval Tassa (CoRR, 2018)

RL Unplugged: A Collection of Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Thomas Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (NeurIPS, 2020)

An empirical investigation of the challenges of real-world reinforcement learning. - Gabriel Dulac-Arnold; Nir Levine; Daniel J. Mankowitz; Jerry Li; Cosmin Paduraru; Sven Gowal; Todd Hester (CoRR, 2020)

RL Unplugged: Benchmarks for Offline Reinforcement Learning. - Çaglar Gülçehre; Ziyu Wang 001; Alexander Novikov 001; Tom Le Paine; Sergio Gómez Colmenarejo; Konrad Zolna; Rishabh Agarwal; Josh Merel; Daniel J. Mankowitz; Cosmin Paduraru; Gabriel Dulac-Arnold; Jerry Li; et al. (CoRR, 2020)

Hyperparameter Selection for Offline Reinforcement Learning. - Tom Le Paine; Cosmin Paduraru; Andrea Michi; Çaglar Gülçehre; Konrad Zolna; Alexander Novikov 001; Ziyu Wang 001; Nando de Freitas (CoRR, 2020)

Robust Constrained Reinforcement Learning for Continuous Control with Model Misspecification. - Daniel J. Mankowitz; Dan A. Calian; Rae Jeong; Cosmin Paduraru; Nicolas Heess; Sumanth Dathathri; Martin A. Riedmiller; Timothy A. Mann (CoRR, 2020)

Benchmarks for Deep Off-Policy Evaluation. - Justin Fu; Mohammad Norouzi 002; Ofir Nachum; George Tucker; Ziyu Wang 001; Alexander Novikov 001; Mengjiao Yang 001; Michael R. Zhang; Yutian Chen 001; Aviral Kumar; Cosmin Paduraru; Sergey Levine; et al. (ICLR, 2021)

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. - Michael R. Zhang; Thomas Paine; Ofir Nachum; Cosmin Paduraru; George Tucker; Ziyu Wang 001; Mohammad Norouzi 002 (ICLR, 2021)

Active Offline Policy Selection. - Ksenia Konyushkova; Yutian Chen 001; Thomas Paine; Çaglar Gülçehre; Cosmin Paduraru; Daniel J. Mankowitz; Misha Denil; Nando de Freitas (NeurIPS, 2021)

Autoregressive Dynamics Models for Offline Policy Evaluation and Optimization. - Michael R. Zhang; Tom Le Paine; Ofir Nachum; Cosmin Paduraru; George Tucker; Ziyu Wang 001; Mohammad Norouzi 002 (CoRR, 2021)

Challenges of real-world reinforcement learning: definitions, benchmarks and analysis. - Gabriel Dulac-Arnold; Nir Levine; Daniel J. Mankowitz; Jerry Li; Cosmin Paduraru; Sven Gowal; Todd Hester (Mach. Learn., 2021)

COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation. - Jongmin Lee 004; Cosmin Paduraru; Daniel J. Mankowitz; Nicolas Heess; Doina Precup; Kee-Eung Kim; Arthur Guez (ICLR, 2022)

Semi-analytical Industrial Cooling System Model for Reinforcement Learning. - Yuri Chervonyi; Praneet Dutta; Piotr Trochim; Octavian Voicu; Cosmin Paduraru; Crystal Qian; Emre Karagozler; Jared Quincy Davis; Richard Chippendale; Gautam Bajaj; Sims Witherspoon; Jerry Luo (CoRR, 2022)

Optimizing Industrial HVAC Systems with Hierarchical Reinforcement Learning. - William Wong; Praneet Dutta; Octavian Voicu; Yuri Chervonyi; Cosmin Paduraru; Jerry Luo (CoRR, 2022)

Controlling Commercial Cooling Systems Using Reinforcement Learning. - Jerry Luo; Cosmin Paduraru; Octavian Voicu; Yuri Chervonyi; Scott Munns; Jerry Li; Crystal Qian; Praneet Dutta; Jared Quincy Davis; Ningjia Wu; Xingwei Yang; Chu-Ming Chang; et al. (CoRR, 2022)

Transformers Meet Directed Graphs. - Simon Geisler; Yujia Li 001; Daniel J. Mankowitz; Ali Taylan Cemgil; Stephan Günnemann; Cosmin Paduraru (ICML, 2023)

Optimizing Memory Mapping Using Deep Reinforcement Learning. - Pengming Wang 001; Mikita Sazanovich; Berkin Ilbeyi; Phitchaya Mangpo Phothilimthana; Manish Purohit; Han Yang Tay; Ngân Vu; Miaosen Wang; Cosmin Paduraru; Edouard Leurent; Anton Zhernov; Julian Schrittwieser; et al. (CoRR, 2023)

Towards practical reinforcement learning for tokamak magnetic control. - Brendan D. Tracey; Andrea Michi; Yuri Chervonyi; Ian Davies; Cosmin Paduraru; Nevena Lazic; Federico Felici; Timo Ewalds; Craig Donner; Cristian Galperti; Jonas Buchli; Michael Neunert; et al. (CoRR, 2023)

Faster sorting algorithms discovered using deep reinforcement learning. - Daniel J. Mankowitz; Andrea Michi; Anton Zhernov; Marco Gelmi; Marco Selvi; Cosmin Paduraru; Edouard Leurent; Shariq Iqbal; Jean-Baptiste Lespiau; Alex Ahern; Thomas Köppe; Kevin Millikin; et al. (Nat., 2023)

Training Language Models to Self-Correct via Reinforcement Learning. - Aviral Kumar; Vincent Zhuang; Rishabh Agarwal; Yi Su; John D. Co-Reyes; Avi Singh; Kate Baumli; Shariq Iqbal; Colton Bishop; Rebecca Roelofs; Lei M. Zhang; Kay McKinney; et al. (ICLR, 2025)