GitHub / konstantinos-p / Bayesian-Neural-Networks-Reading-List
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 details: "A Primer on Bayesian Neural Networks: Review and Debates"
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Created at: over 2 years ago
Updated at: over 1 year ago
Pushed at: over 1 year ago
Last synced at: over 1 year ago
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Mean commits per author: 18.0
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Topics: approximate-inference, bayes-by-backprop, bayesian-inference, bayesian-neural-networks, deep-learning, hmc, kronecker-factored-approximation, langevin-dynamics, local-reparametrization-trick, mcmc, sgld, uncertainty, uncertainty-neural-networks, variational-inference