GitHub / cambridge-mlg / arch_uncert
Code for "Variational Depth Search in ResNets" (https://arxiv.org/abs/2002.02797)
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cambridge-mlg%2Farch_uncert
PURL: pkg:github/cambridge-mlg/arch_uncert
Stars: 9
Forks: 5
Open issues: 0
License: mit
Language: Jupyter Notebook
Size: 5.92 MB
Dependencies parsed at: Pending
Created at: over 5 years ago
Updated at: almost 4 years ago
Pushed at: about 5 years ago
Last synced at: about 1 year ago
Topics: bayesian-deep-learning, bayesian-inference, bayesian-neural-networks, expectation-maximization, fashion-mnist, learnt-depth, mnist, network-compression, network-depths, neural-architecture-search, reproducible-paper, reproducible-research, residual-networks, resnets, sparse-neural-networks, svhn, uncertainty, variational-inference