2 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.CO2025
A Comparison of Kernels for ABC-SMC
Dennis Prangle, Cecilia Viscardi, Sammy Ragy
A popular method for likelihood-free inference is approximate Bayesian computation sequential Monte Carlo (ABC-SMC) algorithms. These approximate the posterior using a population o…