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Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

paper kernel kernels gpytorch regression uncertainty deep-learning meta-learning shot-learning classification kernel-methods bayesian-methods few-shot-learning one-shot-learning gaussian-processes deep-kernel-learning uncertainty-quantification

Created 2019-10-10

53 commits to master branch, last one 2 years ago

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mit

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Gaussian Processes for Experimental Sciences

active-learning machine-learning bayesian-inference gaussian-processes hypothesis-learning deep-kernel-learning bayesian-optimization multi-fidelity-learning bayesian-neural-networks

Created 2021-10-28

787 commits to main branch, last one about a month ago

39

183

mit

11

Deep and Machine Learning for Microscopy

imaging pytorch materials microscopy deep-learning jupyter-notebook machine-learning ensemble-learning materials-science electron-microscopy google-colaboratory deep-kernel-learning multivariate-analysis semantic-segmentation variational-autoencoders scanning-probe-microscopy fully-convolutional-networks

Created 2020-09-04

1,412 commits to master branch, last one 4 months ago