1 citations · 2 across the 4 of their papers we have counts for
3 papers · 1 filter
Evaluating Point-Prediction Uncertainties in Neural Networks for Drug Discovery
Ya Ju Fan, Jonathan E. Allen, Kevin S. McLoughlin +4
Neural Network (NN) models provide potential to speed up the drug discovery process and reduce its failure rates. The success of NN models require uncertainty quantification (UQ) a…
High-Throughput Virtual Screening of Small Molecule Inhibitors for SARS-CoV-2 Protein Targets with Deep Fusion Models
Garrett A. Stevenson, Derek Jones, Hyojin Kim +29
Structure-based Deep Fusion models were recently shown to outperform several physics- and machine learning-based protein-ligand binding affinity prediction methods. As part of a mu…
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency
Ya Ju Fan, Jonathan E. Allen, Sam Ade Jacobs +1
Gene expression profiles have been widely used to characterize patterns of cellular responses to diseases. As data becomes available, scalable learning toolkits become essential to…