variational-inference topic
pymc
Bayesian Modeling and Probabilistic Programming in Python
Bayesian-Neural-Networks
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
PyTorch-BayesianCNN
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
bcpd
Bayesian Coherent Point Drift (BCPD/BCPD++/GBCPD/GBCPD++)
variational-inference-with-normalizing-flows
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
normalizing-flows
PyTorch implementation of normalizing flow models
Deep-Generative-Models-for-Natural-Language-Processing
DGMs for NLP. A roadmap.
Generative_Models_Tutorial_with_Demo
Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important...
normalizing-flows
Understanding normalizing flows
variational-autoencoder
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)