Awesome resources on normalizing flows.
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Updated
Oct 7, 2024 - Python
Awesome resources on normalizing flows.
Deep Learning sample programs using PyTorch in C
Rectified Flow Inversion (RF-Inversion)
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.
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)
Watch faces morph into each other with StyleGAN 2, StyleGAN, and DCGAN!
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.
Reproduction and extension of "Diffusion Models Already Have a Semantic Latent Space" by Kwon et al. (2023).
synthesising Gnawa music (GGm) using WaveGan, a special kind of Adversarial Generative Networks (GANs).
Contains my experimentations with the popular GAN architectures and training methods.
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