Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
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…
cs.LG2025
Direct Molecular Polarizability Prediction with SO(3) Equivariant Local Frame GNNs
Jean Philip Filling, Felix Post, Michael Wand +1
We introduce a novel equivariant graph neural network (GNN) architecture designed to predict the tensorial response properties of molecules. Unlike traditional frameworks that focu…