Machine learning, in numpy

A Collection of Variational Autoencoders (VAE) in PyTorch.

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

Collection of generative models in Tensorflow

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

Advanced Deep Learning with Keras, published by Packt

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

Vector Quantized VAEs - PyTorch Implementation

Experiments for understanding disentanglement in VAE latent representations

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

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

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

Pytorch implementation of β-VAE

Minimalist implementation of VQ-VAE in Pytorch

Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)

Tensorflow implementation of variational auto-encoder for MNIST

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

Pytorch implementation of BERT4Rec and Netflix VAE.

Optimus: the first large-scale pre-trained VAE language model