Leveraging the structure of dynamical systems for data-driven modeling. - Alessandro Bucci; Onofrio Semeraro; Alexandre Allauzen; Sergio Chibbaro; Lionel Mathelin (CoRR, 2021)

Neural State-Dependent Delay Differential Equations. - Thibault Monsel; Onofrio Semeraro; Lionel Mathelin; Guillaume Charpiat (CoRR, 2023)

Enhancing Data-Assimilation in CFD using Graph Neural Networks. - Michele Quattromini; Michele Alessandro Bucci; Stefania Cherubini; Onofrio Semeraro (CoRR, 2023)

Increasing information for model predictive control with semi-Markov decision processes. - Rémy Hosseinkhan Boucher; Stella Douka; Onofrio Semeraro; Lionel Mathelin (L4DC, 2024)

Neural DDEs with Learnable Delays for Partially Observed Dynamical Systems. - Thibault Monsel; Emmanuel Menier; Onofrio Semeraro; Lionel Mathelin; Guillaume Charpiat (CoRR, 2024)

Graph Neural Networks and Differential Equations: A hybrid approach for data assimilation of fluid flows. - Michele Quattromini; Michele Alessandro Bucci; Stefania Cherubini; Onofrio Semeraro (CoRR, 2024)

Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning. - Rémy Hosseinkhan Boucher; Onofrio Semeraro; Lionel Mathelin (CoRR, 2025)

Increasing Information for Model Predictive Control with Semi-Markov Decision Processes. - Rémy Hosseinkhan Boucher; Onofrio Semeraro; Lionel Mathelin (CoRR, 2025)