174 citations · 175 across the 2 of their papers we have counts for
2 papers
cs.LG2022★ 1 cited
Action Matching: Learning Stochastic Dynamics from Samples
Kirill Neklyudov, Rob Brekelmans, Daniel Severo +1
Learning the continuous dynamics of a system from snapshots of its temporal marginals is a problem which appears throughout natural sciences and machine learning, including in quan…
cs.LG2014★ 174 cited
Winner-Take-All Autoencoders
Alireza Makhzani, Brendan Frey
In this paper, we propose a winner-take-all method for learning hierarchical sparse representations in an unsupervised fashion. We first introduce fully-connected winner-take-all a…