Popular GitHub Repositories for Normalizing Flows

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Awesome resources on normalizing flows.

Normalizing flows in PyTorch

An extension of XGBoost to probabilistic modelling

Normalizing flows in PyTorch

PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech

An extension of LightGBM to probabilistic modelling

Normalizing-flow enhanced sampling package for probabilistic inference in Jax

Network-to-Network Translation with Conditional Invertible Neural Networks

Pytorch implementation of Block Neural Autoregressive Flow

Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)

Likelihood-free AMortized Posterior Estimation with PyTorch

A PyTorch implementation of "WaveFlow: A Compact Flow-based Model for Raw Audio" (ICML 2020)

Implementation of Unconstrained Monotonic Neural Network and the related experiments. These architectures are particularly useful for modelling monotonic transformations in normalizing flows.

The official repository of BFSR: "Boosting Flow-based Generative Super-Resolution Models via Learned Prior" [CVPR 2024]

Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)

Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399

Implementation of non-linear independent components estimation (NICE) in pytorch

PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)

[NeurIPS2020] The official repository of "AdvFlow: Inconspicuous Black-box Adversarial Attacks using Normalizing Flows".