A D3R prospective evaluation of machine learning for protein-ligand scoring. - Jocelyn Sunseri; Matthew Ragoza; Jasmine Collins; David Ryan Koes (J. Comput. Aided Mol. Des., 2016)

Ligand Pose Optimization with Atomic Grid-Based Convolutional Neural Networks. - Matthew Ragoza; Lillian Turner; David Ryan Koes (CoRR, 2017)

Protein-Ligand Scoring with Convolutional Neural Networks. - Matthew Ragoza; Joshua E. Hochuli; Elisa Idrobo; Jocelyn Sunseri; David Ryan Koes (J. Chem. Inf. Model., 2017)

Visualizing Convolutional Neural Network Protein-Ligand Scoring. - Joshua E. Hochuli; Alec Helbling; Tamar Skaist; Matthew Ragoza; David Ryan Koes (CoRR, 2018)

Learning a Continuous Representation of 3D Molecular Structures with Deep Generative Models. - Matthew Ragoza; Tomohide Masuda; David Ryan Koes (CoRR, 2020)

Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models. - Tomohide Masuda; Matthew Ragoza; David Ryan Koes (CoRR, 2020)

Generating 3D Molecules Conditional on Receptor Binding Sites with Deep Generative Models. - Matthew Ragoza; Tomohide Masuda; David Ryan Koes (CoRR, 2021)

GNINA 1.0: molecular docking with deep learning. - Andrew T. McNutt; Paul G. Francoeur; Rishal Aggarwal; Tomohide Masuda; Rocco Meli; Matthew Ragoza; Jocelyn Sunseri; David Ryan Koes (J. Cheminformatics, 2021)

Adversarial Consistency for Single Domain Generalization in Medical Image Segmentation. - Yanwu Xu 003; Shaoan Xie; Maxwell Reynolds; Matthew Ragoza; Mingming Gong; Kayhan Batmanghelich (MICCAI (8), 2022)

Physics-Informed Neural Networks for Tissue Elasticity Reconstruction in Magnetic Resonance Elastography. - Matthew Ragoza; Kayhan Batmanghelich (MICCAI (10), 2023)