675 citations · 1.8k across the 55 of their papers we have counts for
Showing 2021 · stat.MLShow all
2 papers · 2 filters
stat.ML2021★ 8 cited
Storchastic: A Framework for General Stochastic Automatic Differentiation
Emile van Krieken, Jakub M. Tomczak, Annette ten Teije
Modelers use automatic differentiation (AD) of computation graphs to implement complex Deep Learning models without defining gradient computations. Stochastic AD extends AD to stoc…
stat.ML2021★ 10 cited
Invertible DenseNets with Concatenated LipSwish
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient extension of Residual Flows. The method relies on an analysis of the Lipschitz continuity of the co…