Search Results for author: Artun Bayer

Found 2 papers, 1 papers with code

Label Propagation across Graphs: Node Classification using Graph Neural Tangent Kernels

no code implementations7 Oct 2021 Artun Bayer, Arindam Chowdhury, Santiago Segarra

In this context, our current work considers a challenging inductive setting where a set of labeled graphs are available for training while the unlabeled target graph is completely separate, i. e., there are no connections between labeled and unlabeled nodes.

Node Classification

GIST: Distributed Training for Large-Scale Graph Convolutional Networks

1 code implementation20 Feb 2021 Cameron R. Wolfe, Jingkang Yang, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis

The graph convolutional network (GCN) is a go-to solution for machine learning on graphs, but its training is notoriously difficult to scale both in terms of graph size and the number of model parameters.

BIG-bench Machine Learning Graph Sampling

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