An Introduction to Graph Neural Networks: Models and Applications

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Microsoft Research
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Published on ● Video Link: https://www.youtube.com/watch?v=zCEYiCxrL_0


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MSR Cambridge, AI Residency Advanced Lecture Series
An Introduction to Graph Neural Networks: Models and Applications

Got it now: "Graph Neural Networks (GNN) are a general class of networks that work over graphs. By representing a problem as a graph — encoding the information of individual elements as nodes and their relationships as edges — GNNs learn to capture patterns within the graph. These networks have been successfully used in applications such as chemistry and program analysis. In this introductory talk, I will do a deep dive in the neural message-passing GNNs, and show how to create a simple GNN implementation. Finally, I will illustrate how GNNs have been used in applications.

https://www.microsoft.com/en-us/research/video/msr-cambridge-lecture-series-an-introduction-to-graph-neural-networks-models-and-applications/



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Tags:
Graph Neural Networks
GNN
neural message-passing GNN
Miltos Allamanis
Patricia Gillespie
Microsoft Research Cambridge