63 citations · 74 across the 2 of their papers we have counts for
2 papers
physics.chem-ph2020★ 63 cited
Molecular Design in Synthetically Accessible Chemical Space via Deep Reinforcement Learning
Julien Horwood, Emmanuel Noutahi
The fundamental goal of generative drug design is to propose optimized molecules that meet predefined activity, selectivity, and pharmacokinetic criteria. Despite recent progress,…
cs.LG2019★ 11 cited
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling
Emmanuel Noutahi, Dominique Beaini, Julien Horwood +2
Recent work in graph neural networks (GNNs) has led to improvements in molecular activity and property prediction tasks. Unfortunately, GNNs often fail to capture the relative impo…