VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech

A Collection of Variational Autoencoders (VAE) in PyTorch.

Collection of generative models in Tensorflow

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

Notebooks about Bayesian methods for machine learning

PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.

Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder

Deep probabilistic analysis of single-cell and spatial omics data

"Deep Generative Modeling": Introductory Examples

My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano

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

The Official PyTorch Implementation of "NVAE: A Deep Hierarchical Variational Autoencoder" (NeurIPS 2020 spotlight paper)

Next RecSys Library

PyTorch implementation of normalizing flow models

A pytorch implementation of the vector quantized variational autoencoder (https://arxiv.org/abs/1711.00937)

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

Experiments for understanding disentanglement in VAE latent representations

[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

generate MNIST using a Variational Autoencoder

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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).

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)

Variational autoencoders for collaborative filtering

Caffe code to accompany my Tutorial on Variational Autoencoders

Tensorflow implementation of variational auto-encoder for MNIST

Variational Recurrent Autoencoder for timeseries clustering in pytorch

This repository contains model-free deep reinforcement learning algorithms implemented in Pytorch

A simple tutorial of Variational AutoEncoders with Pytorch