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Preprint: (Post et al 2026) - Ab initio parametrization of distributed...
We propose a first-principles based parameterization procedure for atomic polarizability tensors and scalars, validated on a set of small set of organic molecules with... -
Publication: (Filling et al 2025) - Direct Molecular Polarizability...
The paper describes a graph neural network architecture that uses local frames to predict local geometric properties.. -
Franzen, Wand (NeurIPS 21) - General Nonlinearities in SO(2)-Equivariant...
Handling general nonlinearities in group-convolutional networks with SO(2)-invariance. -
Publication: Franzen et al (2026) - Discretizing Group-Convolutional Neural...
A paper that describes how to speed-up deep learning on 3D point clouds with (G-)CNNs by compressing its linear representation layers by a local partial symmetry analysis. -
Publication: Filling et al (2026) - Tensor Channel Equivariant Graph Neural...
This paper improves upon the previous paper published at the NeurIPS '25 ML4PhysicalScience-Workshop by using overcomplete generating sets rather than a basis to represent local... -
Publication: Stieffenhofer et al (2022) - Benchmarking coarse-grained models...
Code and datasets related to the publication -
Franzen, Disselhoff, Hartmann (2025) - ICML25 ARC-AGI Challenge Paper
The paper describes the techniques used in the competition for the ARC (Version 1) challenge, which the authors won in 2024. -
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Publication: Melega et al (2026) - A novel implementation of CCSD analytic...
Data related to Melega, L., Nottoli, T., Gauss, J.& Lipparini, F (2026): J. Phys. Chem. A 130, 2097-2111 (2026); Doi:10.1021/acs.jpca.5c08579 (open ac-cess)