1 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.CO2024★ 1 cited
Generalizing self-normalized importance sampling with couplings
Nicola Branchini, Víctor Elvira
An essential problem in statistics and machine learning is the estimation of expectations involving PDFs with intractable normalizing constants. The self-normalized importance samp…
stat.CO2023
Adaptive importance sampling for heavy-tailed distributions via -divergence minimization
Thomas Guilmeau, Nicola Branchini, Emilie Chouzenoux +1
Adaptive importance sampling (AIS) algorithms are widely used to approximate expectations with respect to complicated target probability distributions. When the target has heavy ta…
cs.LG2022★ 1 cited
Causal Entropy Optimization
Nicola Branchini, Virginia Aglietti, Neil Dhir +1
We study the problem of globally optimizing the causal effect on a target variable of an unknown causal graph in which interventions can be performed. This problem arises in many a…