295 Open source projects that are alternatives of or similar to Vae Cvae Mnist

Tensorflow implementation of conditional variational auto-encoder for MNIST

Collection of generative models in Tensorflow

Experiments for understanding disentanglement in VAE latent representations

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

Tensorflow implementation of variational auto-encoder for MNIST

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

Minimalist implementation of VQ-VAE in Pytorch

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

[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)

Implementation of a convolutional Variational-Autoencoder model in pytorch.

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

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Protein function prediction using a variational autoencoder

Tensorflow implementation of Hyperspherical Variational Auto-Encoders

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

No description or website provided.

Assessing Generative Models via Precision and Recall (official repository)

Tensorflow implementation of adversarial auto-encoder for MNIST

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

Learning about Haskell with Variational Autoencoders

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

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

Pytorch implementation of Hyperspherical Variational Auto-Encoders

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

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

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

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.

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

Comparison of Generative Models in Tensorflow

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

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

Deep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)

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

Stochastic Adversarial Video Prediction

Playing with MNIST. Machine Learning. Generative Models.

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

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Invariant representation learning from imaging and spectral data

PyTorch implementation of "Auto-Encoding Variational Bayes"

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

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

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

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

Variational Auto-Encoders in a Sequential Setting.

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

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Focal Frequency Loss for Generative Models

Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10

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

This is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

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

Pytorch implementation of Block Neural Autoregressive Flow

The Pytorch Implementation of L-Softmax

Lingvo

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

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