Accurate and scalable exchange-correlation with deep learning

no code implementations • 17 Jun 2025 • Giulia Luise, Chin-wei Huang, Thijs Vogels, Derk P. Kooi, Sebastian Ehlert, Stephanie Lanius, Klaas J. H. Giesbertz, Amir Karton, Deniz Gunceler, Megan Stanley, Wessel P. Bruinsma, Lin Huang, Xinran Wei, José Garrido Torres, Abylay Katbashev, Rodrigo Chavez Zavaleta, Bálint Máté, Sékou-Oumar Kaba, Roberto Sordillo, Yingrong Chen, David B. Williams-Young, Christopher M. Bishop, Jan Hermann, Rianne van den Berg, Paola Gori-Giorgi

Skala achieves chemical accuracy for atomization energies of small molecules while retaining the computational efficiency typical of semi-local DFT.

Computational Efficiency Deep Learning

Highly Accurate Real-space Electron Densities with Neural Networks

1 code implementation • 2 Sep 2024 • Lixue Cheng, P. Bernát Szabó, Zeno Schätzle, Derk P. Kooi, Jonas Köhler, Klaas J. H. Giesbertz, Frank Noé, Jan Hermann, Paola Gori-Giorgi, Adam Foster

Variational ab-initio methods in quantum chemistry stand out among other methods in providing direct access to the wave function.

Local and global interpolations along the adiabatic connection of DFT: A study at different correlation regimes

no code implementations • 9 Dec 2020 • Derk P. Kooi, Paola Gori-Giorgi

Interpolating the exchange-correlation energy along the density-fixed adiabatic connection of density functional theory is a promising way to build approximations that are not biased towards the weakly correlated regime.

Strongly Correlated Electrons