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cs.LG2022★ 1 cited
ProPaLL: Probabilistic Partial Label Learning
Łukasz Struski, Jacek Tabor, Bartosz Zieliński
Partial label learning is a type of weakly supervised learning, where each training instance corresponds to a set of candidate labels, among which only one is true. In this paper,…
cs.LG2022
Bounding Evidence and Estimating Log-Likelihood in VAE
Łukasz Struski, Marcin Mazur, Paweł Batorski +2
Many crucial problems in deep learning and statistical inference are caused by a variational gap, i.e., a difference between model evidence (log-likelihood) and evidence lower boun…