PyTorch implementation of normalizing flow models

Official PyTorch code for Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021)

Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data

Official implementation of GLARE, which is accpeted by ECCV 2024.

This is project page for the paper "RG-Flow: a hierarchical and explainable flow model based on renormalization group and sparse prior". Paper link: https://arxiv.org/abs/2010.00029

Regularized Neural ODEs (RNODE)

Pytorch source code for arXiv paper Neural Network Renormalization Group, a generative model using variational renormalization group and normalizing flow.

Official code base of "Perception-Oriented Video Frame Interpolation via Asymmetric Blending" (CVPR 2024), also denoted as ''PerVFI''.

Flow Annealed Importance Sampling Bootstrap (FAB). ICLR 2023.

PyTorch implementation of the Masked Autoregressive Flow

Code for "Style-Structure Disentangled Features and Normalizing Flows for Diverse Icon Colorization", CVPR 2022.

A pytorch implementation for FACE: A Normalizing Flow based Cardinality Estimator

A minimal working example of Free-Form Jacobian of Reversible Dynamics

Modern normalizing flows in Python. Simple to use and easily extensible.

In this repo, I developed a step-by-step pipeline for a standard MultiSpeaker Text-to-Speech system 😄 In general, I used Portaspeech as an acoustic model and iSTFTNet as vocoder...

(Conditional) Normalizing Flows in PyTorch. Offers a wide range of (conditional) invertible neural networks.

"FS-NCSR: Increasing Diversity of the Super-Resolution Space via Frequency Separation and Noise-Conditioned Normalizing Flow" (CVPRW 2022)

TensorFlow implementation of "Variational Inference with Normalizing Flows"

TensorFlow implementation of Normalizing Flow

Sliced Iterative Normalizing Flow with Minimal Dependencies