vae

Machine learning, in numpy

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

DeepNude's algorithm and general image generation theory and practice research, including pix2pix, CycleGAN, UGATIT, DCGAN, SinGAN, ALAE, mGANprior, StarGAN-v2 and VAE models (TensorFlow2 implementation). DeepNude的算法以及通用生成对抗网络（GAN,Generative Adversarial Network）图像生成的理论与实践研究。

A Collection of Variational Autoencoders (VAE) in PyTorch.

Collection of generative models in Tensorflow

Advanced Deep Learning with Keras, published by Packt

Diffusion model papers, survey, and taxonomy

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.

Experiments for understanding disentanglement in VAE latent representations

Vector Quantized VAEs - PyTorch Implementation

A collection of generative methods implemented with TensorFlow (Deep Convolutional Generative Adversarial Networks (DCGAN), Variational Autoencoder (VAE) and DRAW: A Recurrent Neural Network For Image Generation).

PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349

VPoser: Variational Human Pose Prior

This is the repository of our article published in RecSys 2020 "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" and of several follow-up studies.

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN

Tensorflow implementation of variational auto-encoder for MNIST

Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟