mattjj / svae
code for Structured Variational Autoencoders
☆349Updated 6 years ago
Related projects ⓘ
Alternatives and complementary repositories for svae
- Structured Inference Networks for Nonlinear State Space Models☆265Updated 7 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆208Updated 8 years ago
- Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆204Updated 8 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Implementation of a Variational Auto-Encoder in Theano☆378Updated 7 years ago
- Probabilistic Torch is library for deep generative models that extends PyTorch☆887Updated 6 months ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 6 years ago
- ☆290Updated 6 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆192Updated 5 years ago
- ☆153Updated 5 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆376Updated 7 years ago
- Deep generative models for semi-supervised learning.☆109Updated 8 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆386Updated 8 months ago
- Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"☆518Updated 5 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆99Updated 8 years ago
- Code for "Sequential Neural Models with Stochastic Layers"☆115Updated 8 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆107Updated 7 years ago
- Code for reproducing results of NIPS 2014 paper "Semi-Supervised Learning with Deep Generative Models"☆509Updated 9 years ago
- Dropout As A Bayesian Approximation: Code☆199Updated 9 years ago
- Fast C code for sampling Polya-gamma random variates. Builds on Jesse Windle's BayesLogit library.☆82Updated 4 years ago
- Implementation of VLAE☆215Updated 6 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆247Updated 3 months ago
- Implementation of Variational Auto-Encoder in Torch7☆267Updated 7 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- A variational recurrent neural network implementation in tensorflow☆104Updated 6 years ago
- Unsupervised clustering with (Gaussian mixture) VAEs☆295Updated 7 years ago
- ☆90Updated 6 years ago
- Generative moment matching networks☆149Updated 8 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆106Updated 6 years ago
- Deep Generative Models with Stick-Breaking Priors☆94Updated 8 years ago