HIPS / Probabilistic-BackpropagationLinks
Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.
☆191Updated 6 years ago
Alternatives and similar repositories for Probabilistic-Backpropagation
Users that are interested in Probabilistic-Backpropagation are comparing it to the libraries listed below
Sorting:
- Variational and semi-supervised neural network toppings for Lasagne☆210Updated 9 years ago
- Optimizers for machine learning☆182Updated 2 years ago
- Exploring differentiation with respect to hyperparameters☆295Updated 9 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆207Updated 9 years ago
- Python package for modular Bayesian optimization☆137Updated 4 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆107Updated 7 years ago
- Deep exponential families (DEFs)☆55Updated 7 years ago
- Efficient implementation of Generative Stochastic Networks☆318Updated 9 years ago
- Flexible Bayesian inference using TensorFlow☆142Updated 8 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models.☆43Updated 11 years ago
- Dropout As A Bayesian Approximation: Code☆204Updated 10 years ago
- What My Deep Model Doesn't Know...☆116Updated 10 years ago
- code for stochastic expectation propagation☆16Updated 9 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation☆128Updated 4 years ago
- Repo for a paper about constructing priors on very deep models.☆73Updated 9 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated last year
- Deep generative models for semi-supervised learning.☆109Updated 8 years ago
- Implements SFO minibatch optimizer in Python and MATLAB, and reproduces figures from paper.☆129Updated 4 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆380Updated 8 years ago
- Probabilistic Programming and Statistical Inference in PyTorch☆111Updated 8 years ago
- Collaborative filtering with the GP-LVM☆25Updated 10 years ago
- code for Structured Variational Autoencoders☆351Updated 7 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- Stochastic gradient routines for Theano☆103Updated 7 years ago
- Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"☆130Updated 8 years ago
- Introduction to Nonparametric Bayes, Infinite Mixture Models, and the Dirichlet Process (+ McDonald's)☆306Updated 10 years ago
- repository for the Variational Autoencoder (VAE) blogpost series from Fast Forward Labs☆103Updated 8 years ago