6 citations · 12 across the 3 of their papers we have counts for
3 papers
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari
Rationalizing which parts of a molecule drive the predictions of a molecular graph convolutional neural network (GCNN) can be difficult. To help, we propose two simple regularizati…
Gini in a Bottleneck: Sparse Molecular Representations for Graph Convolutional Neural Networks
Ryan Henderson, Djork-Arné Clevert, Floriane Montanari
Due to the nature of deep learning approaches, it is inherently difficult to understand which aspects of a molecular graph drive the predictions of the network. As a mitigation str…
Picasso: A Modular Framework for Visualizing the Learning Process of Neural Network Image Classifiers
Ryan Henderson, Rasmus Rothe
Picasso is a free open-source (Eclipse Public License) web application written in Python for rendering standard visualizations useful for analyzing convolutional neural networks. P…