About
I am a PhD student in Electrical Engineering at KTH Royal Institute of Technology in Stockholm, Sweden, co-advised by Mikael Skoglund and Tobias Oechtering. My doctoral research is supported by the WASP Graduate School, where I am pursuing the joint curriculum in Artificial Intelligence and Autonomous Systems. Before my PhD, I completed a double master’s degree in Applied and Computational Mathematics at KTH and École Polytechnique de Louvain, as well as a bachelor’s degree in Applied Mathematics and Electrical engineering at École Polytechnique de Louvain.
In 2024, I had the opportunity to work as a Visiting Student Researcher at Stanford University under the supervision of Professor Benjamin Van Roy.
My research interests are at the intersection of reinforcement learning and information theory. Specifically, I am studying the performance of the Thompson Sampling algorithm for bandit problems.
I am always open to discussing topics in information theory and machine learning, so please feel free to reach out if you would like to connect.
Publications (Chronological)
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, An Information-Theoretic Analysis of Thompson Sampling for Logistic Bandits
Accepted at NeurIPS 2024 Workshop on "Bayesian Decision-making and Uncertainty" | pdf
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, An Information-Theoretic Analysis of Thompson Sampling with Infinite Action Spaces
Submitted to ICASSP 2025 | pdf
Raghav Bongole, Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality
Submitted to ICASSP 2025 | pdf
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, Chained Information-Theoretic bounds and Tight Regret Rate for Linear Bandit Problems
Presented at FoRLaC Workshop at ICML 2024 | arXiv | pdf
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, Thompson Sampling Regret Bounds for Contextual Bandits with sub-Gaussian rewards
Presented at ISIT 2023 | arXiv | pdf | conference pdf
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering, and Mikael Skoglund, An Information-Theoretic Analysis of Bayesian Reinforcement Learning
Presented at Allerton 2022 | arXiv | pdf | conference pdf
Antoine Aspeel, Amaury Gouverneur, Raphaël M. Jungers, and Benoit Macq, Optimal intermittent particle filter
IEEE Transactions on Signal Processing 2022 | arXiv | pdf | journal pdf
Amaury Gouverneur, Optimal measurement times for particle filtering and its application in mobile tumor tracking
Master Thesis 2022, Prom.: Benoit Macq | dial | pdf
Antoine Aspeel, Amaury Gouverneur, Raphaël M. Jungers, and Benoit Macq, Optimal measurement budget allocation for particle filtering
Presented at ICIP 2020 arXiv | pdf | conference pdf
Teaching
Project in Multimedia Processing and Analysis, EQ2445, KTH at KTH - 2024
Machine Learning and Data Science, EQ2415, KTH at KTH - 2024
Pattern Recognition and Machine Learning, EQ2341, KTH at KTH - 2020-2024
Deep Neural Networks, EP232U at KTH - Spring 2022
Service
Reviewing service for for EUSIPCO (2022-2023), ICML 2024, ICASSP 2025, ICLR 2025
WASP Cluster leader for "Mathematical Foundations of AI other than ML" (2020-2024)
WASP Cluster leader for "Sequential Decision-Making and Reinforcement Learning" (current)
Bachelor Thesis Supervision:
- Reza Qorbani and Kevin Pettersson - Investigation of Information-Theoretic Bounds on Generalization Error