Smart exploration in reinforcement learning using absolute temporal difference errors. - Clement Gehring; Doina Precup (AAMAS, 2013)

Incremental Truncated LSTD. - Clement Gehring; Martha White (CoRR, 2015)

Incremental Truncated LSTD. - Clement Gehring; Yangchen Pan; Martha White (IJCAI, 2016)

Batched Large-scale Bayesian Optimization in High-dimensional Spaces. - Zi Wang 004; Clement Gehring; Pushmeet Kohli; Stefanie Jegelka (AISTATS, 2018)

Adaptable replanning with compressed linear action models for learning from demonstrations. - Clement Gehring; Leslie Pack Kaelbling; Tomás Lozano-Pérez (CoRL, 2018)

Robust Reinforcement Learning: A Constrained Game-theoretic Approach. - Jing Yu; Clement Gehring; Florian Schäfer; Animashree Anandkumar (L4DC, 2021)

Understanding End-to-End Model-Based Reinforcement Learning Methods as Implicit Parameterization. - Clement Gehring; Kenji Kawaguchi; Jiaoyang Huang; Leslie Pack Kaelbling (NeurIPS, 2021)

Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators. - Clement Gehring; Masataro Asai; Rohan Chitnis; Tom Silver; Leslie Pack Kaelbling; Shirin Sohrabi; Michael Katz 001 (ICAPS, 2022)

Efficient reinforcement learning via singular value decomposition, end-to-end model-based methods and reward shaping - Clement Gehring (2022)

Course Correcting Koopman Representations. - Mahan Fathi; Clement Gehring; Jonathan Pilault; David Kanaa; Pierre-Luc Bacon; Ross Goroshin (ICLR, 2024)

Bridging State and History Representations: Understanding Self-Predictive RL. - Tianwei Ni; Benjamin Eysenbach; Erfan Seyedsalehi; Michel Ma; Clement Gehring; Aditya Mahajan; Pierre-Luc Bacon (ICLR, 2024)

Do Transformer World Models Give Better Policy Gradients? - Michel Ma; Tianwei Ni; Clement Gehring; Pierluca D'Oro; Pierre-Luc Bacon (ICML, 2024)

Functional Risk Minimization. - Ferran Alet; Clement Gehring; Tomás Lozano-Pérez; Kenji Kawaguchi; Joshua B. Tenenbaum; Leslie Pack Kaelbling (CoRR, 2024)