variational-inference

SoftVC VITS Singing Voice Conversion

Bayesian Modeling and Probabilistic Programming in Python

Deep universal probabilistic programming with Python and PyTorch

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

Gaussian processes in TensorFlow

Awesome resources on normalizing flows.

Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

Seminars DeepBayes Summer School 2018

Python package for point cloud registration using probabilistic model (Coherent Point Drift, GMMReg, SVR, GMMTree, FilterReg, Bayesian CPD)

Boltzmann Machines in TensorFlow with examples

PyTorch implementation of normalizing flow models

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

[NeurIPS 2022] Denoising Diffusion Restoration Models -- Official Code Repository

A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.

Lecture notes on Bayesian deep learning

Statistical Rethinking (2nd ed.) with NumPyro

DGMs for NLP. A roadmap.

Generative Models Tutorial with Demo: Bayesian Classifier Sampling, Variational Auto Encoder (VAE), Generative Adversial Networks (GANs), Popular GANs Architectures, Auto-Regressive Models, Important Generative Model Papers, Courses, etc..

Julia package for automated Bayesian inference on a factor graph with reactive message passing