Awesome resources on normalizing flows.

Rectified Flow Inversion (RF-Inversion)

Deep Learning sample programs using PyTorch in C++

Regression Transformer (2023; Nature Machine Intelligence)

Unofficial Implementation of "Denoising Diffusion Probabilistic Models" in PyTorch(Lightning)

The repository contains reproducible PyTorch source code of our paper Generative Modeling with Optimal Transport Maps, ICLR 2022.

Ying Nian Wu's UCLA Statistical Machine Learning Tutorial on generative modeling.

Flow-based generative model for 3D point clouds.

Code for the paper Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.

ECCV 2024 SuperGaussian for generic 3D upsampling

Noise Contrastive Estimation (NCE) in PyTorch

Multiplicative Normalizing Flows in PyTorch.

[AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".

Official code for Continuous-Time Functional Diffusion Processes (NeurIPS 2023).

Official Implementation of Paper "Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling" (ICML 2023)

The official repository for NeurIPS 2024 Oral <Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models>

Watch faces morph into each other with StyleGAN 2, StyleGAN, and DCGAN!

[NeurIPS 2024] Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation

Code accompanying "Generative Models: An Interdisciplinary Perspective"

The code for the paper "Incentivizing Collaboration in Machine Learning via Synthetic Data Rewards" AAAI'22 Oral Presentation.