Riccardo De Santi

According to our database, Riccardo De Santi authored at least 15 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Constrained Flow Optimization via Sequential Fine Tuning for Molecular Design.

Sven Gutjahr, Riccardo De Santi, Luca Schaufelberger, Kjell Jorner, Andreas Krause

CoRR, May, 2026

Efficient Tail-Aware Generative Optimization via Flow Model Fine-Tuning.

Zifan Wang, Riccardo De Santi, Xiaoyu Mo, Michael M. Zavlanos, Andreas Krause, Karl Henrik Johansson

CoRR, February, 2026

Verifier-Constrained Flow Expansion for Discovery Beyond the Data.

Riccardo De Santi, Kimon Protopapas, Ya-Ping Hsieh, Andreas Krause

CoRR, February, 2026

A Unified Density Operator View of Flow Control and Merging.

Riccardo De Santi, Malte Franke, Ya-Ping Hsieh, Andreas Krause

CoRR, February, 2026

2025

Efficient Personalization of Generative Models via Optimal Experimental Design.

Guy Schacht, Ziyad Sheebaelhamd, Riccardo De Santi, Mojmír Mutný, Andreas Krause

CoRR, December, 2025

Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning.

Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

CoRR, November, 2025

Landing with the Score: Riemannian Optimization through Denoising.

Andrey Kharitenko, Zebang Shen, Riccardo De Santi, Niao He, Florian Dörfler

CoRR, September, 2025

Provable Maximum Entropy Manifold Exploration via Diffusion Models.

Riccardo De Santi, Marin Vlastelica, Ya-Ping Hsieh, Zebang Shen, Niao He, Andreas Krause

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Global Reinforcement Learning : Beyond Linear and Convex Rewards via Submodular Semi-gradient Methods.

Riccardo De Santi, Manish Prajapat, Andreas Krause

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Geometric Active Exploration in Markov Decision Processes: the Benefit of Abstraction.

Riccardo De Santi, Federico Arangath Joseph, Noah Liniger, Mirco Mutti, Andreas Krause

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning.

Mirco Mutti, Riccardo De Santi, Marcello Restelli, Alexander Marx, Giorgia Ramponi

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Convex Reinforcement Learning in Finite Trials.

Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

J. Mach. Learn. Res., 2023

Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization.

Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Challenging Common Assumptions in Convex Reinforcement Learning.

Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

The Importance of Non-Markovianity in Maximum State Entropy Exploration.

Mirco Mutti, Riccardo De Santi, Marcello Restelli

Proceedings of the International Conference on Machine Learning, 2022