1.7k citations · 4.5k across the 53 of their papers we have counts for
54 papers
Folding@home: achievements from over twenty years of citizen science herald the exascale era
Vincent A. Voelz, Vijay S. Pande, Gregory R. Bowman
Simulations of biomolecules have enormous potential to inform our understanding of biology but require extremely demanding calculations. For over twenty years, the Folding@home dis…
Classical Quantum Optimization with Neural Network Quantum States
Joseph Gomes, Keri A. McKiernan, Peter Eastman +1
The classical simulation of quantum systems typically requires exponential resources. Recently, the introduction of a machine learning-based wavefunction ansatz has led to the abil…
Physical machine learning outperforms "human learning" in Quantum Chemistry
Anton V. Sinitskiy, Vijay S. Pande
Two types of approaches to modeling molecular systems have demonstrated high practical efficiency. Density functional theory (DFT), the most widely used quantum chemical method, is…
Predicting Gene Expression Between Species with Neural Networks
Peter Eastman, Vijay S. Pande
We train a neural network to predict human gene expression levels based on experimental data for rat cells. The network is trained with paired human/rat samples from the Open TG-GA…
Strategies for Pre-training Graph Neural Networks
Weihua Hu, Bowen Liu, Joseph Gomes +4
Many applications of machine learning require a model to make accurate pre-dictions on test examples that are distributionally different from training ones, while task-specific lab…
Step Change Improvement in ADMET Prediction with PotentialNet Deep Featurization
Evan N. Feinberg, Robert Sheridan, Elizabeth Joshi +2
The Absorption, Distribution, Metabolism, Elimination, and Toxicity (ADMET) properties of drug candidates are estimated to account for up to 50% of all clinical trial failures. Pre…