There are 24 repositories under normalizing-flows topic.
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Awesome resources on normalizing flows.
Normalizing flows in PyTorch
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
An extension of XGBoost to probabilistic modelling
DGMs for NLP. A roadmap.
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech
Normalizing flows in PyTorch
Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
Repository for Deep Structural Causal Models for Tractable Counterfactual Inference
An extension of LightGBM to probabilistic modelling
Manifold-learning flows (â„ł-flows)
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Code for reproducing Flow ++ experiments
Pytorch implementation of Block Neural Autoregressive Flow
A Julia framework for invertible neural networks
Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
Understanding normalizing flows
Real NVP PyTorch a Minimal Working Example | Normalizing Flow
Official code for "Maximum Likelihood Training of Score-Based Diffusion Models", NeurIPS 2021 (spotlight)
Likelihood-free AMortized Posterior Estimation with PyTorch
Discrete Normalizing Flows implemented in PyTorch
Code for the paper "Improving Variational Auto-Encoders using Householder Flow" (https://arxiv.org/abs/1611.09630)
[CVPR 2023] Code repository for HuManiFlow: Ancestor-Conditioned Normalising Flows on SO(3) Manifolds for Human Pose and Shape Distribution Estimation
Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" https://arxiv.org/abs/1904.02399
A Python Library for Deep Probabilistic Modeling