NeurIPS 2015poster4663 citations
Convolutional Networks on Graphs for Learning Molecular Fingerprints
David K. Duvenaud, Dougal Maclaurin, Jorge Iparraguirre, Rafael Bombarell, Timothy Hirzel, Alan Aspuru-Guzik, Ryan P. Adams
Abstract
We introduce a convolutional neural network that operates directly on graphs.These networks allow end-to-end learning of prediction pipelines whose inputs are graphs of arbitrary size and shape.The architecture we present generalizes standard molecular feature extraction methods based on circular fingerprints.We show that these data-driven features are more interpretable, and have better predictive performance on a variety of tasks.
BibTeX
@inproceedings{NIPS2015_f9be311e,
author = {Duvenaud, David K and Maclaurin, Dougal and Iparraguirre, Jorge and Bombarell, Rafael and Hirzel, Timothy and Aspuru-Guzik, Alan and Adams, Ryan P},
booktitle = {Advances in Neural Information Processing Systems},
editor = {C. Cortes and N. Lawrence and D. Lee and M. Sugiyama and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Convolutional Networks on Graphs for Learning Molecular Fingerprints},
url = {https://proceedings.neurips.cc/paper_files/paper/2015/file/f9be311e65d81a9ad8150a60844bb94c-Paper.pdf},
volume = {28},
year = {2015}
}