In this work, we propose the novel Prototypical Graph Regression
Self-ex...
Self-supervised learning holds promise to revolutionize molecule propert...
Recent years have seen a surge in research on deep interpretable neural
...
Graph neural networks have recently become a standard method for analysi...
We investigate the problem of training neural networks from incomplete i...
Designing a single neural network architecture that performs competitive...
Graph Convolutional Networks (GCNs) have recently become the primary cho...