Optimal Measurement Budget Allocation For Particle Filtering. - Antoine Aspeel; Amaury Gouverneur; Raphaël M. Jungers; Benoît Macq (ICIP, 2020)

An Information-Theoretic Analysis of Bayesian Reinforcement Learning. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (Allerton, 2022)

Optimal Intermittent Particle Filter. - Antoine Aspeel; Amaury Gouverneur; Raphaël M. Jungers; Benoît Macq (IEEE Trans. Signal Process., 2022)

Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ISIT, 2023)

Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2024)

An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2024)

Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality. - Raghav Bongole; Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ICASSP, 2025)

An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces. - Amaury Gouverneur; Borja Rodríguez Gálvez; Tobias J. Oechtering; Mikael Skoglund (ICASSP, 2025)

Refined PAC-Bayes Bounds for Offline Bandits. - Amaury Gouverneur; Tobias J. Oechtering; Mikael Skoglund (CoRR, 2025)