3 papers
stat.ML2026
Full Bayesian Reinforcement Learning via LF-IBIS
Stefano Masini, Cecilia Viscardi, Michela Baccini
Reinforcement Learning (RL) is a sequential decision-making framework in which an agent learns optimal policies through interaction with an environment by maximizing cumulative rew…
stat.ME2024
Forecasting Causal Effects of Future Interventions: Confounding and Transportability Issues
Laura Forastiere, Fan Li, Michela Baccini
Recent developments in causal inference allow us to transport a causal effect of a time-fixed treatment from a randomized trial to a target population across space but within the s…
stat.AP2016
Potential outcome approach to causal inference in assessing the short term impact of air pollution on mortality
Michela Baccini, Alessandra Mattei, Fabrizia Mealli +2
The opportunity to assess short term impact of air pollution relies on the causal interpretation of the exposure-outcome association, but up to now few studies explicitly faced thi…