675 citations · 1.8k across the 55 of their papers we have counts for
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cs.LG2016★ 82 cited
Improving Variational Auto-Encoders using Householder Flow
Jakub M. Tomczak, Max Welling
Variational auto-encoders (VAE) are scalable and powerful generative models. However, the choice of the variational posterior determines tractability and flexibility of the VAE. Co…
stat.ML2016★ 110 cited
Learning Deep Architectures for Interaction Prediction in Structure-based Virtual Screening
Adam Gonczarek, Jakub M. Tomczak, Szymon Zaręba +3
We introduce a deep learning architecture for structure-based virtual screening that generates fixed-sized fingerprints of proteins and small molecules by applying learnable atom c…