2 citations · 2 across the 2 of their papers we have counts for
2 papers
stat.ML2026
Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation
Andrea Basteri, Carlo Ciliberto, Alessandro Rudi
Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametric assumptions that ignore the…
cs.LG2022★ 2 cited
Quantitative Gaussian Approximation of Randomly Initialized Deep Neural Networks
Andrea Basteri, Dario Trevisan
Given any deep fully connected neural network, initialized with random Gaussian parameters, we bound from above the quadratic Wasserstein distance between its output distribution a…