174 Open source projects that are alternatives of or similar to Cada Vae Pytorch

Tensorflow implementation of conditional variational auto-encoder for MNIST

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

Pytorch implementation of Hyperspherical Variational Auto-Encoders

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

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

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

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

Experiments for understanding disentanglement in VAE latent representations

Assessing Generative Models via Precision and Recall (official repository)

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.

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

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

Stochastic Adversarial Video Prediction

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

Collection of generative models in Tensorflow

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Invariant representation learning from imaging and spectral data

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"

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

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

Implementation of a convolutional Variational-Autoencoder model in pytorch.

PyTorch implementation of "Auto-Encoding Variational Bayes"

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

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

Tensorflow implementation of variational auto-encoder for MNIST

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

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

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

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

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

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

[CVPR 2017] Generation and reconstruction of 3D shapes via modeling multi-view depth maps or silhouettes

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

Variational auto-encoder trained on celebA . All rights reserved.

Focal Frequency Loss for Generative Models

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

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

Comparison of Generative Models in Tensorflow

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

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

A Tensorfflow implementation of Attend, Infer, Repeat

Simple implementation of Variational Autoencoder

Pytorch implementation of Block Neural Autoregressive Flow

Notebooks about Bayesian methods for machine learning

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

Variational Autoencoder trained by Feature Perceputal Loss

Implementation of CodeSLAM — Learning a Compact, Optimisable Representation for Dense Visual SLAM paper (https://arxiv.org/pdf/1804.00874.pdf)

PyTorch implementation of latent space reinforcement learning for E2E dialog published at NAACL 2019. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU

Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano

Deep Recurrent Generative Decoder for Abstractive Text Summarization in DyNet

Training and evaluating a variational autoencoder for pan-cancer gene expression data

The original implementation of the models and experiments of Variational Deep Semantic Hashing paper (SIGIR 2017)

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

Understanding normalizing flows