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
Pytorch implementations of density estimation algorithms: BNAF, Glow, MAF, RealNVP, planar flows
Normalizing flows in PyTorch
An extension of LightGBM to probabilistic modelling
PyTorch Implementation of PortaSpeech: Portable and High-Quality Generative Text-to-Speech
Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
Official PyTorch code for WACV 2022 paper "CFLOW-AD: Real-Time Unsupervised Anomaly Detection with Localization via Conditional Normalizing Flows"
Normalizing-flow enhanced sampling package for probabilistic inference in Jax
Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
Network-to-Network Translation with Conditional Invertible Neural Networks
Code for reproducing Flow ++ experiments
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
pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation
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