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Found 3 papers, 2 papers with code
Analysis of Sparse Subspace Clustering: Experiments and Random Projection
Clustering can be defined as the process of assembling objects into a number of groups whose elements are similar to each other in some manner.
Attentive Walk-Aggregating Graph Neural Networks
Our experiments demonstrate the strong performance of AWARE in graph-level prediction tasks in the standard setting in the domains of molecular property prediction and social networks.
Graph Neural Networks for an Accurate and Interpretable Prediction of the Properties of Polycrystalline Materials
Various machine learning models have been used to predict the properties of polycrystalline materials, but none of them directly consider the physical interactions among neighboring grains despite such microscopic interactions critically determining macroscopic material properties.
Materials Science
