Kevin Ryczko
FX Palo Alto Laboratory(US)
Publications by Year
Research Areas
Machine Learning in Materials Science, Computational Drug Discovery Methods, Neural Networks and Applications, Catalysis and Oxidation Reactions, X-ray Diffraction in Crystallography
Most-Cited Works
- → Deep learning and density-functional theory(2019)123 cited
- → Extensive deep neural networks for transferring small scale learning to large scale systems(2019)57 cited
- → Convolutional neural networks for atomistic systems(2018)46 cited
- → Toward Orbital-Free Density Functional Theory with Small Data Sets and Deep Learning(2022)45 cited
- → Crystal Site Feature Embedding Enables Exploration of Large Chemical Spaces(2020)43 cited
- → Accelerated Organic Crystal Structure Prediction with Genetic Algorithms and Machine Learning(2023)19 cited
- → Twin neural network regression(2022)17 cited
- → Machine Learning Diffusion Monte Carlo Energies(2022)16 cited
- → Inverse Design of a Graphene-Based Quantum Transducer via Neuroevolution(2020)13 cited
- → Guided multi-objective generative AI to enhance structure-based drug design(2025)10 cited