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Post #441

@graphml

Graph Machine Learning

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Publié23 févr.23/02/2021 10:49
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Fresh picks from ArXiv This week on ArXiv: improved generalization bound, deblurring images with Laplacians, and new datasets for drug discovery 💊 If I forgot to mention your paper, please shoot me a message and I will update the post. GNNs * Generalization bounds for graph convolutional neural networks via Rademacher complexity * SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolution Networks * Dissecting the Diffusion Process in Linear Graph Convolutional Networks * E(n) Equivariant Graph Neural Networks with Max Welling * Combinatorial optimization and reasoning with graph neural networks with Petar Veličković * Topological Graph Neural Networks with Karsten Borgwardt Applications * Graph Laplacian for image deblurring * Interpretable Stability Bounds for Spectral Graph Filters * On the Similarity between von Neumann Graph Entropy and Structural Information: Interpretation, Computation, and Applications * A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective with William Hamilton