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GraphLearning

swMATH ID: 42962
Software Authors: Calder, J.
Description: GraphLearning Python package: This python package is devoted to efficient implementations of modern graph-based learning algorithms for both semi-supervised learning and clustering. The package implements many popular datasets (currently MNIST, FashionMNIST, and CIFAR-10) in a way that makes it simple for users to test out new algorithms and rapidly compare against existing methods. Full documentation is available, including detailed example scripts. This package also reproduces experiments from the paper: J. Calder, B. Cook, M. Thorpe, D. Slepcev. Poisson Learning: Graph Based Semi-Supervised Learning at Very Low Label Rates., Proceedings of the 37th International Conference on Machine Learning, PMLR 119:1306-1316, 2020.
Homepage: http://proceedings.mlr.press/v119/calder20a/calder20a.pdf
Dependencies: Python
Related Software: Fashion-MNIST; EMNIST; MNIST
Referenced in: 1 Publication

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