Electron-Density-Informed Molecular Property Prediction Using Surrogate Functionals
physics.chem-ph, cs.LG
Submitted: 2026-10-09
Updated: 2026-10-09
Sources
- Enhancing molecular dynamics with equivariant machine-learned densities
- Fast and Uncertainty-Aware Directional Message Passing for Non-Equilibrium Molecules
- Directional Message Passing for Molecular Graphs
- Equivariant Graph Attention Networks for Molecular Property Prediction
Related papers
- Solvating machine-learning interatomic potentials for solution-phase chemistry
- Transferable Generative Models Bridge Femtosecond to Nanosecond Time-Step Molecular Dynamics
- Accelerated "on-the-fly" coupled-cluster path-integral molecular dynamics: Impact of nuclear quantum effects on an asymmetric proton
- Learning Non-Local Molecular Interactions via Equivariant Local Representations and Charge Equilibration
- Variational Polaron Theory for Ground States of Strongly Coupled Light-Matter and Electron-Phonon Systems
- Pushing the accuracy of on-top functionals with agent-driven supervised learning