GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design Abstract: Graph Convolutional Networks (GCNs) have emerged as the state-of-the-art graph learning model ...

To address these challenges, we propose a novel algorithm that extends SSC to cocluster large HSIs, called bipartite graph partition with graph nonnegative matrix factorization (BGP-GNMF).

Using this information, the model can then tell us the probability of a drug-protein interaction that we did not previously ...

By learning the relevant features of clinical images along with the relationships between them, the neural network can outperform more traditional methods.