Awesome resources on normalizing flows.
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Updated
Apr 12, 2024 - Python
Awesome resources on normalizing flows.
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.
[AISTATS2020] The official repository of "Invertible Generative Modling using Linear Rational Splines (LRS)".
Noise Contrastive Estimation (NCE) in PyTorch
Multiplicative Normalizing Flows in PyTorch.
StrangeR things: Creating Generative Art… with R?. How to create Generative Art without much effort and without being an artist with the "aRtsy" package
Code for the paper Iterated Denoising Energy Matching for Sampling from Boltzmann Densities.
Code accompanying "Generative Models: An Interdisciplinary Perspective"
Official Implementation of Paper "Learning to Jump: Thinning and Thickening Latent Counts for Generative Modeling" (ICML 2023)
Official code for Continuous-Time Functional Diffusion Processes (NeurIPS 2023).
Official source code repository for the paper "Benchmarking Generative Latent Variable Models for Speech"
This repository is a comprehensive guide and toolkit for music generation, featuring diverse algorithms, deep learning models, and creative techniques to inspire and assist in the composition of unique musical pieces.
Watch faces morph into each other with StyleGAN 2, StyleGAN, and DCGAN!
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