2 papers
stat.ML2022
Optimality in Noisy Importance Sampling
Fernando Llorente, Luca Martino, Jesse Read +1
In this work, we analyze the noisy importance sampling (IS), i.e., IS working with noisy evaluations of the target density. We present the general framework and derive optimal prop…
stat.CO2020
Adaptive quadrature schemes for Bayesian inference via active learning
F. Llorente, L. Martino, V. Elvira +2
Numerical integration and emulation are fundamental topics across scientific fields. We propose novel adaptive quadrature schemes based on an active learning procedure. We consider…