402 Open source projects that are alternatives of or similar to Variational Recurrent Autoencoder Tensorflow

A CNN Variational Autoencoder (CNN-VAE) implemented in PyTorch

Assessing Generative Models via Precision and Recall (official repository)

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

Invariant representation learning from imaging and spectral data

Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.

music generation with a classifying variational autoencoder (VAE) and LSTM

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

Stochastic Adversarial Video Prediction

Tensorflow implementation of conditional variational auto-encoder for MNIST

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

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Keras implementation of a Variational Auto Encoder with a Concrete Latent Distribution

Pytorch implementation of Hyperspherical Variational Auto-Encoders

IPCCC 2018: Robust and Unsupervised KPI Anomaly Detection Based on Conditional Variational Autoencoder

Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets

Tensorflow implementation of variational auto-encoder for MNIST

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

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).

Text Variational Autoencoder inspired by the paper 'Generating Sentences from a Continuous Space' Bowman et al. https://arxiv.org/abs/1511.06349

There are C language computer programs about the simulator, transformation, and test statistic of continuous Bernoulli distribution. More than that, the book contains continuous Binomial distribution and continuous Trinomial distribution.

Collection of generative models in Tensorflow

VAE with RealNVP prior and Super-Resolution VAE in PyTorch. Code release for https://arxiv.org/abs/2006.05218.

PyTorch implementation of "Auto-Encoding Variational Bayes"

Protein function prediction using a variational autoencoder

[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE: Analyzing and Improving Introspective Variational Autoencoders"

Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090

PyTorch code for CVIU paper "AC-VRNN: Attentive Conditional-VRNN for Multi-Future Trajectory Prediction"

Experiments for understanding disentanglement in VAE latent representations

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Implementation of a convolutional Variational-Autoencoder model in pytorch.

An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU) in ICLR 2017.

Official implementation of the paper "Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders" (CVPR 2019)

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

If you've always wanted to learn about deep-learning but don't know where to start, then you might have stumbled upon the right place!

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

Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.

A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).

brain.js is a GPU accelerated library for Neural Networks written in JavaScript.

HDLTex: Hierarchical Deep Learning for Text Classification

How to build RNNs and LSTMs from scratch with NumPy.

PyTorch Implementation of "A Hierarchical Latent Structure for Variational Conversation Modeling" (NAACL 2018 Oral)

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press

Replicating "Understanding disentangling in β-VAE"

PyTorch implementation of "Lagging Inference Networks and Posterior Collapse in Variational Autoencoders" (ICLR 2019)

Layer-wise Relevance Propagation (LRP) for LSTMs

Unofficial PyTorch Implementation of SUM-GAN from "Unsupervised Video Summarization with Adversarial LSTM Networks" (CVPR 2017)

Recurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.

Semi-Supervised Video Object Segmentation (VOS) with Tensorflow. Includes implementation of *MaskRNN: Instance Level Video Object Segmentation (NIPS 2017)* as part of the NIPS Paper Implementation Challenge.

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

This is the end-to-end Speech Recognition neural network, deployed in Keras. This was my final project for Artificial Intelligence Nanodegree @Udacity.

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

Variational Autoencoder for Dimensionality Reduction of Time-Series

A Collection of Variational Autoencoders (VAE) in PyTorch.

Anomaly detection for temporal data using LSTMs

The first public PyTorch implementation of Attentive Recurrent Comparators

Blend beats using machine learning to create music in a fun new way.

Pytorch implementation of FactorVAE proposed in Disentangling by Factorising(http://arxiv.org/abs/1802.05983)

Variational Auto-Encoders in a Sequential Setting.