SCISSORS: Practical Considerations. - Steven M. Kearnes; Imran S. Haque; Vijay S. Pande (J. Chem. Inf. Model., 2014)

Massively Multitask Networks for Drug Discovery. - Bharath Ramsundar; Steven Kearnes; Patrick Riley 001; Dale Webster; David E. Konerding; Vijay S. Pande (CoRR, 2015)

Molecular graph convolutions: moving beyond fingerprints. - Steven Kearnes; Kevin McCloskey; Marc Berndl; Vijay S. Pande; Patrick Riley 001 (J. Comput. Aided Mol. Des., 2016)

ROCS-derived features for virtual screening. - Steven Kearnes; Vijay S. Pande (J. Comput. Aided Mol. Des., 2016)

Osprey: Hyperparameter Optimization for Machine Learning. - Robert T. McGibbon; Carlos X. Hernández; Matthew P. Harrigan; Steven Kearnes; Mohammad M. Sultan; Stanislaw Jastrzebski; Brooke E. Husic; Vijay S. Pande (J. Open Source Softw., 2016)

Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds. - Nathaniel Thomas; Tess E. Smidt; Steven Kearnes; Lusann Yang; Li Li 060; Kai Kohlhoff; Patrick Riley 001 (CoRR, 2018)

Optimization of Molecules via Deep Reinforcement Learning. - Zhenpeng Zhou; Steven Kearnes; Li Li 060; Richard N. Zare; Patrick Riley 001 (CoRR, 2018)

Decoding Molecular Graph Embeddings with Reinforcement Learning. - Steven Kearnes; Li Li 060; Patrick Riley 001 (CoRR, 2019)

Machine learning on DNA-encoded libraries: A new paradigm for hit-finding. - Kevin McCloskey; Eric A. Sigel; Steven Kearnes; Ling Xue; Xia Tian; Dennis Moccia; Diana Gikunju; Sana Bazzaz; Betty Chan; Matthew A. Clark 004; John W. Cuozzo; Marie-Aude Guié; et al. (CoRR, 2020)

Energy-based View of Retrosynthesis. - Ruoxi Sun 002; Hanjun Dai; Li Li 060; Steven Kearnes; Bo Dai 001 (CoRR, 2020)

Pursuing a Prospective Perspective. - Steven Kearnes (CoRR, 2020)

Towards understanding retrosynthesis by energy-based models. - Ruoxi Sun 002; Hanjun Dai; Li Li 060; Steven Kearnes; Bo Dai 001 (NeurIPS, 2021)

Data Sharing in Chemistry: Lessons Learned and a Case for Mandating Structured Reaction Data. - Rocío Mercado; Steven M. Kearnes; Connor W. Coley (J. Chem. Inf. Model., 2023)

Ordinal Confidence Level Assignments for Regression Model Predictions. - Steven Kearnes; Patrick Riley 001 (J. Chem. Inf. Model., 2024)