1 citations · 2 across the 9 of their papers we have counts for
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Neuron Activation-based Computation of Logical Explanations for Deep Neural Networks
Tomáš Kolárik, Faezeh Labbaf, Fabrizio Leopardi +3
Formal explainability of classifying neural networks (NNs) is an active area of research, providing explanations with provable guarantees of the classification within continuous re…
Ab initio parametrization of distributed polarizable force fields
Felix Post, Jean-Philip Filling, Toulik Maitra +3
Polarizable force fields offer superior transferability and accuracy compared to classical force fields, enabling access to electronic response properties such as refractive index…
Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction
Jean Philip Filling, Daniel Franzen, Michael Wand
We introduce a tensor-channel equivariant graph neural network for direct prediction of molecular polarizability tensors. Building on the efficient PaiNN architecture, we augment t…
Reconstruction of spin structures from topological charge distributions via generative neural network systems
Kyra H. M. Klos, Jan Disselhoff, Michael Wand +2
Localized topological defects inherently possess a multiscale character. While their microstructure configuration depends on the specific physical system, their topological feature…