Karl Leswing
Schrodinger (United States)(US)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Protein Structure and Dynamics, Chemical Synthesis and Analysis, Fuel Cells and Related Materials
Most-Cited Works
- → MoleculeNet: a benchmark for molecular machine learning(2017)2,817 cited
- → Efficient Exploration of Chemical Space with Docking and Deep Learning(2021)375 cited
- → Epik: p K a and Protonation State Prediction through Machine Learning(2023)278 cited
- → Reaction-Based Enumeration, Active Learning, and Free Energy Calculations To Rapidly Explore Synthetically Tractable Chemical Space and Optimize Potency of Cyclin-Dependent Kinase 2 Inhibitors(2019)137 cited
- → High-Dimensional Neural Network Potential for Liquid Electrolyte Simulations(2022)85 cited
- → Combining Cloud-Based Free-Energy Calculations, Synthetically Aware Enumerations, and Goal-Directed Generative Machine Learning for Rapid Large-Scale Chemical Exploration and Optimization(2020)55 cited
- → Transferable Neural Network Potential Energy Surfaces for Closed-Shell Organic Molecules: Extension to Ions(2022)53 cited
- → Design of Organic Electronic Materials With a Goal-Directed Generative Model Powered by Deep Neural Networks and High-Throughput Molecular Simulations(2022)35 cited
- → Development of scalable and generalizable machine learned force field for polymers(2023)24 cited