1 citations · 1 across the 4 of their papers we have counts for
7 papers
How Molecular Generative Models Organize Molecular Identity
Raul Ortega-Ochoa, Tejs Vegge, Jens S. Bakander +3
Generative models for matter are often evaluated as samplers over output representations, and their latent spaces are commonly used as proxies for navigating chemical space. Much l…
HIP: Hessian Interatomic Potentials without derivatives
Andreas Burger, Luca Thiede, Nikolaj Rønne +6
Molecular Hessians, the second derivatives of the potential energy, are fundamental to many workflows in computational chemistry. Usually, accurate Hessians are computationally exp…
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
Jonas Elsborg, Felix Ãrtebjerg, Luca Thiede +3
We introduce ELECTRAFI, a fast, end-to-end differentiable model for predicting periodic charge densities in crystalline materials. ELECTRAFI constructs anisotropic Gaussians in rea…
El Agente Sólido: A New Age(nt) for Solid State Simulations
Sai Govind Hari Kumar, Yunheng Zou, Andrew Wang +8
Quantum chemistry calculations are a key component of the materials discovery process. The results from first-principles explorations enable the prediction of material properties p…
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals
Jonas Elsborg, Luca Thiede, Alán Aspuru-Guzik +2
We present the Electronic Tensor Reconstruction Algorithm (ELECTRA) - an equivariant model for predicting electronic charge densities using floating orbitals. Floating orbitals are…
DEQuify your force field: More efficient simulations using deep equilibrium models
Andreas Burger, Luca Thiede, Alán Aspuru-Guzik +1
Machine learning force fields show great promise in enabling more accurate molecular dynamics simulations compared to manually derived ones. Much of the progress in recent years wa…