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Introduction to graph representation learning, including methods for embedding graph data, graph neural networks, and deep generative models of graphs.

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2020-03-30 · A breakdown of the inner workings of GNNs.

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2020-06-14 · Introduce a series of effective graph-structured networks, including non-local neural networks, spatial generalized propagation networks, etc.

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2020-04-23 · Novel approaches based on the theme of structuring the representations and computations of neural network-based models in the form of a graph.

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2020-07-20 · A Temporal Extension Library for PyTorch Geometric

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2020-06-19 · A general approach to distill symbolic representations of a learned deep model by introducing strong inductive biases.

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Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x.

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2020-07-31 · The mechanism of propagating information between neighbors creates a bottleneck when every node aggregates messages from its neighbors.

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2019-12-04 · A Comprehensive Survey on Graph Neural Networks.

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2020-09-12 · My engineering friends often ask me: deep learning on graphs sounds great, but are there any real applications?

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