21 citations · 31 across the 8 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 9 cited
CrysMMNet: Multimodal Representation for Crystal Property Prediction
Kishalay Das, Pawan Goyal, Seung-Cheol Lee +2
Machine Learning models have emerged as a powerful tool for fast and accurate prediction of different crystalline properties. Exiting state-of-the-art models rely on a single modal…
cs.LG2023★ 1 cited
CrysGNN : Distilling pre-trained knowledge to enhance property prediction for crystalline materials
Kishalay Das, Bidisha Samanta, Pawan Goyal +3
In recent years, graph neural network (GNN) based approaches have emerged as a powerful technique to encode complex topological structure of crystal materials in an enriched repres…