Showing 5 of 5 projects
A curated collection of graph classification papers with reference implementations covering embedding, deep learning, kernels, and factorization.
A curated collection of graph classification papers with implementations covering embeddings, deep learning, kernels, and factorization.
A high-level neural network API for specifying and analyzing infinite-width neural networks as Gaussian Processes in Python.
A fast and versatile implementation of support vector machines with integrated hyper-parameter selection and support for multiple learning scenarios.
Composable kernels for scikit-learn implemented in JAX, enabling faster kernel computations and automatic differentiation.
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