This is the Graph Neural Networks: Hands-on Session from the Stanford 2019 Fall CS224W course.
In this tutorial, we will explore the implementation of graph neural networks and investigate what representations these networks learn. Along the way, we'll see how PyTorch Geometric and TensorBoardX can help us with constructing and training graph models.
Pytorch Geometric tutorial part starts at -- 0:33:30
Details on:
* Graph Convolutional Neural Networks (GCN)
* Custom Convolutional Model
* Message passing
* Aggregation functions
* Update
* Graph Pooling
A minimal surface is the surface of minimal area between any given boundaries. In nature such shapes result from an equilibrium of homogeneous tension, e.g. in a soap film. Minimal surfaces have a constant mean curvature of zero, i.e. the sum of the principal curvatures at each point is zero. Particularly fascinating are minimal surfaces…
It is a live weekly hour-long webseries showcasing geometry processing research. Topics range from computer science, mathematics, and engineering including 3D deep learning, computational fabrication, and computer graphics. The unique format of the Toronto Geometry Colloquium pairs a 10-min opener speaking about a recent work with a 50-min headliner giving a keynote-style address
- Aug. 19 – Aug. 28, 2020
- Nike Sun (Massachusetts Institute of Technology; chair), Jian Ding (University of Pennsylvania), Ronen Eldan (Weizmann Institute), Elchanan Mossel (Massachusetts Institute of Technology), Joe Neeman (University of Texas at Austin), Jelani Nelson (UC Berkeley), Tselil Schramm (Stanford University; Microsoft Research Fellow)
J. Heiberg (Eds.) Bibliotheca scriptorum graecorum et romanorum teubneriana (BT) In Aedibvs B.G. Tevbneri MCMLXXII, Stvtgardiae, Editio stereotypa editionis anni MCMX edition, (1972)
C. Ptolemaeus. Felicibus astris eat in lucem: Ductu Petri Liechtenstein Coloniensis Germani. Anno Virginei Partus .1515. Die .10. Ia. Venetiis ex officina eiusdem litteraria, Venetiis, (1515)