289 citations
- Cornell UniversityUS7 papers
- Memorial Sloan Kettering Cancer CenterUS6 papers
- Asahi Kasei (Japan)JP3 papers
- University of Colorado BoulderUS3 papers
- New York UniversityUS2 papers
- Open Geospatial ConsortiumUS2 papers
- University of California, IrvineUS2 papers
- Weill Cornell MedicineUS2 papers
- Asahi Kasei Therapeutics Corporation (Japan)JP1 paper
- City College of New YorkUS1 paper
- City University of New YorkUS1 paper
- Columbia UniversityUS1 paper
9 papers
Wasserstein Wormhole: Scalable Optimal Transport Distance with Transformers
Doron Haviv, Russell Zhang Kunes, Thomas Dougherty +4
Optimal transport (OT) and the related Wasserstein metric (W) are powerful and ubiquitous tools for comparing distributions. However, computing pairwise Wasserstein distances rapid…
Machine-learned molecular mechanics force field for the simulation of protein-ligand systems and beyond
Kenichiro Takaba, Iván Pulido, Pavan Kumar Behara +11
The development of reliable and extensible molecular mechanics (MM) force fields -- fast, empirical models characterizing the potential energy surface of molecular systems -- is in…
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Suraj Rajendran, Weishen Pan, Mert R. Sabuncu +3
Machine learning (ML) in healthcare presents numerous opportunities for enhancing patient care, population health, and healthcare providers' workflows. However, the real-world clin…
EspalomaCharge: Machine learning-enabled ultra-fast partial charge assignment
Yuanqing Wang, Iván Pulido, Kenichiro Takaba +4
Atomic partial charges are crucial parameters in molecular dynamics (MD) simulation, dictating the electrostatic contributions to intermolecular energies, and thereby the potential…
Bayesian inference-driven model parameterization and model selection for 2CLJQ fluid models
Owen C. Madin, Simon Boothroyd, Richard A. Messerly +3
A high level of physical detail in a molecular model improves its ability to perform high accuracy simulations, but can also significantly affect its complexity and computational c…
End-to-End Differentiable Molecular Mechanics Force Field Construction
Yuanqing Wang, Josh Fass, Benjamin Kaminow +6
Molecular mechanics (MM) potentials have long been a workhorse of computational chemistry. Leveraging accuracy and speed, these functional forms find use in a wide variety of appli…