116 Open source projects that are alternatives of or similar to vae_captioning

Variational Auto-Encoders in a Sequential Setting.

Machine learning, in numpy

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

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

Variational Autoencoder trained by Feature Perceputal Loss

Stochastic Adversarial Video Prediction

State Representation Learning (SRL) zoo with PyTorch - Part of S-RL Toolbox

Code accompanying ISMIR'19 paper titled "Learning to Traverse Latent Spaces for Musical Score Inpaintning"

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

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

Paper collection of Neural Text Generation

No description or website provided.

A Collection of Variational Autoencoders (VAE) in PyTorch.

DeepGTT: Learning Travel Time Distributions with Deep Generative Model

Tensorflow implementation of conditional variational auto-encoder for MNIST

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

O-GAN: Extremely Concise Approach for Auto-Encoding Generative Adversarial Networks

Tensorflow implementation of adversarial auto-encoder for MNIST

Tacotron 2 - PyTorch implementation with faster-than-realtime inference modified to enable cross lingual voice cloning.

PyTorch implementation of VQ-VAE by Aäron van den Oord et al.

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

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

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Replicating "Understanding disentangling in β-VAE"

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

(beta-)VAE Tensorflow

Keras implementations of three language models: character-level RNN, word-level RNN and Sentence VAE (Bowman, Vilnis et al 2016).

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

Assessing Generative Models via Precision and Recall (official repository)

Official PyTorch implementation of "Deep State Space Models for Nonlinear System Identification", 2020.

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

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

Code for EMNLP18 paper "Spherical Latent Spaces for Stable Variational Autoencoders"

VPoser: Variational Human Pose Prior

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

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

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

A tensorflow implementation of "Generating Sentences from a Continuous Space"

Deep Learning sample programs using PyTorch in C++

dcgan combined with vae in pytorch!

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

Minimalist implementation of VQ-VAE in Pytorch

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

EfficientMORL (ICML'21)

Comparison of Generative Models in Tensorflow

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

A Tensorfflow implementation of Attend, Infer, Repeat

Implementation of a convolutional Variational-Autoencoder model in pytorch.

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"

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

PyTorch study

Implementation of the paper - Automatic chemical design using a data-driven continuous representation of molecules

Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI

Playing with MNIST. Machine Learning. Generative Models.

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