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stat.ML2024
Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
Edward Milsom, Ben Anson, Laurence Aitchison
Recent work developed convolutional deep kernel machines, achieving 92.7% test accuracy on CIFAR-10 using a ResNet-inspired architecture, which is SOTA for kernel methods. However,…
stat.ML2024
Flexible Infinite-Width Graph Convolutional Neural Networks
Ben Anson, Edward Milsom, Laurence Aitchison
A common theoretical approach to understanding neural networks is to take an infinite-width limit, at which point the outputs become Gaussian process (GP) distributed. This is know…