mattjj / svaeLinks
code for Structured Variational Autoencoders
☆350Updated 6 years ago
Alternatives and similar repositories for svae
Users that are interested in svae are comparing it to the libraries listed below
Sorting:
- Structured Inference Networks for Nonlinear State Space Models☆272Updated 7 years ago
- Variational and semi-supervised neural network toppings for Lasagne☆208Updated 8 years ago
- This repository contains the code to reproduce the core results from the paper "Adversarial Variational Bayes: Unifying Variational Autoe…☆206Updated 7 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Implementation of a Variational Auto-Encoder in Theano☆380Updated 8 years ago
- Code for the paper "A Theoretically Grounded Application of Dropout in Recurrent Neural Networks"☆378Updated 8 years ago
- Code to train Importance Weighted Autoencoders on MNIST and OMNIGLOT☆206Updated 9 years ago
- ☆291Updated 7 years ago
- Code for reproducing results of NIPS 2014 paper "Semi-Supervised Learning with Deep Generative Models"☆515Updated 10 years ago
- Implementation in C and Theano of the method Probabilistic Backpropagation for scalable Bayesian inference in deep neural networks.☆192Updated 6 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
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 11 months ago
- Code for "Sequential Neural Models with Stochastic Layers"☆117Updated 8 years ago
- Generative moment matching networks☆150Updated 9 years ago
- Implementation of VLAE☆215Updated 7 years ago
- A structured list of resources about Sum-Product Networks (SPNs)☆254Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆404Updated last year
- Dropout As A Bayesian Approximation: Code☆202Updated 10 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- Code for reproducing key results in the paper "Improving Variational Inference with Inverse Autoregressive Flow"☆521Updated 6 years ago
- Deep Generative Models with Stick-Breaking Priors☆95Updated 9 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 8 years ago
- Implementation of Sequential Variational Autoencoder☆88Updated 7 years ago
- Implementation of Variational Auto-Encoder in Torch7☆267Updated 8 years ago
- Replicating "Understanding disentangling in β-VAE"☆198Updated 7 years ago
- Optimizing control variates for black-box gradient estimation☆163Updated 5 years ago
- Tools for loading standard data sets in machine learning☆204Updated 2 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