2 papers
physics.chem-ph2026
Projected Hessian Learning: Fast Curvature Supervision for Accurate Machine-Learning Interatomic Potentials
Austin Rodriguez, Justin S. Smith, Sakib Matin +3
The Hessian matrix (second derivatives) encodes far richer local curvature of the potential energy surface than energies and forces alone. However, training machine-learning intera…
physics.chem-ph2025
Does Hessian Data Improve the Performance of Machine Learning Potentials?
Austin Rodriguez, Justin S. Smith, Jose L. Mendoza-Cortes
Integrating machine learning into reactive chemistry, materials discovery, and drug design is revolutionizing the development of novel molecules and materials. Machine Learning Int…