JavierAntoran/Bayesian-Neural-Networks
Pytorch implementations of various Bayesian neural network techniques for approximate inference and uncertainty quantification.
Jupyter Notebook
AI & Machine Learning
ML Ops
MIT
2.0K
Stars
306
Forks
Mar 11, 2019
Created
Oct 20, 2023
Last Updated
Project Analytics
Stars Growth (1 Month)
+5
+0.3% change
Avg Daily Growth (1 Month)
+0.2
stars per day
Fork/Star Ratio (All Time)
15.6%
Good engagement
Lifetime Growth
0.8
stars/day over 2.6K days
Stars Over Time
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Topics
approximate-inference
bayes-by-backprop
bayesian-inference
bayesian-neural-networks
classification
deep-learning
hmc
kronecker-factored-approximation
langevin-dynamics
local-reparametrization-trick
mc-dropout
mcmc
out-of-distribution-detection
pytorch
regression
reproducible-research
sgld
uncertainty
uncertainty-neural-networks
variational-inference
AI-Generated Tags
bayesian-inference
uncertainty-quantification
reproducible-research
deep-learning
classification
regression
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