A production-oriented skill library for AI coding agents working in computational chemistry, materials modeling, atomistic simulation, scientific machine learning, continuum modeling, thermodynamics, ...
A production-oriented skill library for AI coding agents working in computational chemistry, materials modeling, atomistic simulation, scientific machine learning, continuum modeling, thermodynamics, ...
Abstract: Counterfactual subgraphs explain graph neural networks (GNNs) by answering the question: “How would the prediction change if a certain subgraph were absent in the input instance?” The ...
Abstract: Deep graph learning models have recently been developed to learn from various graphs that are prevalent in describing and modeling complex systems, including those in bioinformatics. However ...
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