MatterVial combines pretrained graph-network latent features, compressed descriptors, and SISSO formulas to make MODNet competitive with state-of-the-art GNNs on MatBench with improved interpretability.
F., Florea, L., De Oliveira, M
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Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability
MatterVial combines pretrained graph-network latent features, compressed descriptors, and SISSO formulas to make MODNet competitive with state-of-the-art GNNs on MatBench with improved interpretability.