68 citations · 107 across the 4 of their papers we have counts for
4 papers
Mofasa: A Step Change in Metal-Organic Framework Generation
Vaidotas Simkus, Anders Christensen, Steven Bennett +5
Mofasa is an all-atom latent diffusion model with state-of-the-art performance for generating Metal-Organic Frameworks (MOFs). These are highly porous crystalline materials used to…
ML Models of Vibrating HCO: Comparing Reproducing Kernels, FCHL and PhysNet
Silvan Käser, Debasish Koner, Anders S. Christensen +2
Machine Learning (ML) has become a promising tool for improving the quality of atomistic simulations. Using formaldehyde as a benchmark system for intramolecular interactions, a co…
Neural networks and kernel ridge regression for excited states dynamics of CHNH: From single-state to multi-state representations and multi-property machine learning models
Julia Westermayr, Felix A. Faber, Anders S. Christensen +2
Excited-state dynamics simulations are a powerful tool to investigate photo-induced reactions of molecules and materials and provide complementary information to experiments. Since…
Operator quantum machine learning: Navigating the chemical space of response properties
Anders S. Christensen, O. Anatole von Lilienfeld
The identification and use of structure property relationships lies at the heart of the chemical sciences. Quantum mechanics forms the basis for the unbiased virtual exploration of…