no code implementations • 22 Mar 2024 • Guillem Simeon, Antonio Mirarchi, Raul P. Pelaez, Raimondas Galvelis, Gianni de Fabritiis
In this letter, we present an extension to TensorNet, a state-of-the-art equivariant Cartesian tensor neural network potential, allowing it to handle charged molecules and spin states without architectural changes or increased costs.
1 code implementation • 27 Feb 2024 • Raul P. Pelaez, Guillem Simeon, Raimondas Galvelis, Antonio Mirarchi, Peter Eastman, Stefan Doerr, Philipp Thölke, Thomas E. Markland, Gianni de Fabritiis
Achieving a balance between computational speed, prediction accuracy, and universal applicability in molecular simulations has been a persistent challenge.
2 code implementations • NeurIPS 2023 • Guillem Simeon, Gianni de Fabritiis
The development of efficient machine learning models for molecular systems representation is becoming crucial in scientific research.
Ranked #1 on Formation Energy on QM9
no code implementations • 19 Oct 2022 • Xabier Morales, Jordi Mill, Guillem Simeon, Kristine A. Juhl, Ole De Backer, Rasmus R. Paulsen, Oscar Camara
The assessment of left atrial appendage (LAA) thrombogenesis has experienced major advances with the adoption of patient-specific computational fluid dynamics (CFD) simulations.