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stat.ML2022
Data Subsampling for Bayesian Neural Networks
Eiji Kawasaki, Markus Holzmann, Lawrence Adu-Gyamfi
Markov Chain Monte Carlo (MCMC) algorithms do not scale well for large datasets leading to difficulties in Neural Network posterior sampling. In this paper, we propose Penalty Baye…
stat.ML2022
Discretely Indexed Flows
Elouan Argouarc'h, François Desbouvries, Eric Barat +2
In this paper we propose Discretely Indexed flows (DIF) as a new tool for solving variational estimation problems. Roughly speaking, DIF are built as an extension of Normalizing Fl…