yaringal / DropoutUncertaintyDemosLinks
What My Deep Model Doesn't Know...
☆116Updated 9 years ago
Alternatives and similar repositories for DropoutUncertaintyDemos
Users that are interested in DropoutUncertaintyDemos are comparing it to the libraries listed below
Sorting:
- Dropout As A Bayesian Approximation: Code☆203Updated 10 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆192Updated 6 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated last year
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 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 to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆206Updated 9 years ago
- ☆90Updated 7 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆208Updated 8 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Structured Inference Networks for Nonlinear State Space Models☆273Updated 7 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆106Updated 7 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- Bayesian Weight Uncertainty Dense Layer for Keras☆48Updated 8 years ago
- Deep generative models for semi-supervised learning.☆108Updated 8 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- ☆69Updated 7 years ago
- code for Structured Variational Autoencoders☆350Updated 6 years ago
- Exploring differentiation with respect to hyperparameters☆296Updated 9 years ago
- Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"☆130Updated 7 years ago
- repository for the Variational Autoencoder (VAE) blogpost series from Fast Forward Labs☆103Updated 8 years ago