9 citations · 9 across the 4 of their papers we have counts for
4 papers
CheMLFlow: An Open-Source Platform for Cheminformatics and Materials Informatics Applications
Brendan Smith, Susana Lopez-Moreno, Eric Dolores-Cuenca +3
CheMLFlow is an open-source platform for building and executing end-to-end, high-throughput, and agentic workflows for scientific and technological applications. CheMLFlow targets…
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…
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…
Order Theory in the Context of Machine Learning
Eric Dolores-Cuenca, Aldo Guzman-Saenz, Sangil Kim +2
The paper ``Tropical Geometry of Deep Neural Networks'' by L. Zhang et al. introduces an equivalence between integer-valued neural networks (IVNN) with and tropic…