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Pursuing a Prospective Perspective


Aug 26, 2020
Steven Kearnes


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Energy-based View of Retrosynthesis


Jul 14, 2020
Ruoxi Sun, Hanjun Dai, Li Li, Steven Kearnes, Bo Dai


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Machine learning on DNA-encoded libraries: A new paradigm for hit-finding


Jan 31, 2020
Kevin McCloskey, Eric A. Sigel, Steven Kearnes, Ling Xue, Xia Tian, Dennis Moccia, Diana Gikunju, Sana Bazzaz, Betty Chan, Matthew A. Clark, John W. Cuozzo, Marie-Aude Guié, John P. Guilinger, Christelle Huguet, Christopher D. Hupp, Anthony D. Keefe, Christopher J. Mulhern, Ying Zhang, Patrick Riley


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Decoding Molecular Graph Embeddings with Reinforcement Learning


Apr 18, 2019
Steven Kearnes, Li Li, Patrick Riley

* Preliminary work. Under review at the ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Data. Copyright 2019 by the author(s) 

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Optimization of Molecules via Deep Reinforcement Learning


Oct 23, 2018
Zhenpeng Zhou, Steven Kearnes, Li Li, Richard N. Zare, Patrick Riley

* Adds Supporting Information 

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Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds


May 18, 2018
Nathaniel Thomas, Tess Smidt, Steven Kearnes, Lusann Yang, Li Li, Kai Kohlhoff, Patrick Riley

* changes for NIPS submission 

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Modeling Industrial ADMET Data with Multitask Networks


Jan 13, 2017
Steven Kearnes, Brian Goldman, Vijay Pande

* See "Version information" section 

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ROCS-Derived Features for Virtual Screening


Aug 22, 2016
Steven Kearnes, Vijay Pande

* See "Version information" section 

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Molecular Graph Convolutions: Moving Beyond Fingerprints


Aug 18, 2016
Steven Kearnes, Kevin McCloskey, Marc Berndl, Vijay Pande, Patrick Riley

* J Comput Aided Mol Des (2016) 
* See "Version information" section 

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Massively Multitask Networks for Drug Discovery


Feb 06, 2015
Bharath Ramsundar, Steven Kearnes, Patrick Riley, Dale Webster, David Konerding, Vijay Pande

* Preliminary work. Under review by the International Conference on Machine Learning (ICML) 

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