2 papers
cs.LG2022
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules
Jong Youl Choi, Pei Zhang, Kshitij Mehta +2
Graph Convolutional Neural Network (GCNN) is a popular class of deep learning (DL) models in material science to predict material properties from the graph representation of molecu…
cs.DC2021
Campaign Knowledge Network: Building Knowledge for Campaign Efficiency
Sachith Withana, Kshitij Mehta, Matthew Wolf +1
In the landscape of exascale computing collaborative research campaigns are conducted as co-design activities of loosely coordinated experiments. But the higher level context and t…