yaringal / DropoutUncertaintyDemos
What My Deep Model Doesn't Know...
☆117Updated 9 years ago
Alternatives and similar repositories for DropoutUncertaintyDemos:
Users that are interested in DropoutUncertaintyDemos are comparing it to the libraries listed below
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Dropout As A Bayesian Approximation: Code☆201Updated 9 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- code for stochastic expectation propagation☆16Updated 9 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 8 years ago
- Deep GPs with GPy☆31Updated 8 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆192Updated 6 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 3 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- ☆40Updated 5 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆208Updated 8 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 8 months ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆206Updated 9 years ago
- Deep generative models for semi-supervised learning.☆108Updated 8 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- ☆15Updated 9 years ago
- TensorFlow implementation of Bayes-by-Backprop algorithm from "Weight Uncertainty in Neural Networks" paper☆51Updated 6 years ago
- Code for some of the experiments I did with variational autoencoders on multi-modality and atari video prediction. Atari video prediction…☆62Updated 8 years ago