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Bayesian-Neural-Networks
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Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
pytorch_MCMC
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Lightweight MCMC sampling for PyTorch Models aka My Corona Project
Contour-Stochastic-Gradient-Langevin-Dynamics
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An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
Bayesian-Neural-Networks-Reading-List
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A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesian Deep Learning, by providing an overview of key papers. More...