Repository for "Known Unknowns: Uncertainty Quality in Bayesian Neural Networks" paper.
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Updated
Mar 3, 2017 - Jupyter Notebook
Repository for "Known Unknowns: Uncertainty Quality in Bayesian Neural Networks" paper.
Edward Bayesian Neural Network
Code for training and testing a Hidden Parameter Markov Decision Process, used to facilitate the transfer of learning
PyTorch Implementations of Dropout Variants
Edward implementation of Bayesian Neural Networks
Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.
Implementing a bayesian neural network in TensorFlow
Deep Probabilistic Programming Examples in Pytorch using pyro
Python 3.7 version of David Barber's MATLAB BRMLtoolbox
Thesis: Detecting Adversaries in DQNs and Computer Vision using Bayesian CNNs
Super Resolution using Bayesian CNN
Bayesian Gradient Descent Algorithm Model for TensorFlow
A naive bayesian classifier which tells you if an ICO is a scam based on it's whitepaper abstract
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
Reusable, Easy-to-use Uncertainty module package built with Tensorflow, Keras
A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
A comparison between Bayesian Neural Network and Classical Neural Network
Neural Network based Stochastic Blockmodel using Variational Inference
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