variational-autoencoder
There are 950 repositories under variational-autoencoder topic.
sqvae
Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE)
vde
Variational Autoencoder for Dimensionality Reduction of Time-Series
MuseMorphose
PyTorch implementation of MuseMorphose (published at IEEE/ACM TASLP), a Transformer-based model for music style transfer.
Unsupervised_Anomaly_Detection_Brain_MRI
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study
vae-celebA
Variational auto-encoder trained on celebA . All rights reserved.
BNAF
Pytorch implementation of Block Neural Autoregressive Flow
numalogic
Collection of operational time series ML models and tools
tybalt
Training and evaluating a variational autoencoder for pan-cancer gene expression data
Synthesize3DviaDepthOrSil
[CVPR 2017] Generation and reconstruction of 3D shapes via modeling multi-view depth maps or silhouettes
multimodal-vae-public
A PyTorch implementation of "Multimodal Generative Models for Scalable Weakly-Supervised Learning" (https://arxiv.org/abs/1802.05335)
rectorch
rectorch is a pytorch-based framework for state-of-the-art top-N recommendation
tensorflow-mnist-CVAE
Tensorflow implementation of conditional variational auto-encoder for MNIST
NeuralDialog-LaRL
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
pyraug
Data Augmentation with Variational Autoencoders (TPAMI)
Deep-Learning-for-Clustering-in-Bioinformatics
Deep Learning-based Clustering Approaches for Bioinformatics
Deep-learning-with-Python
Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
kvae
Kalman Variational Auto-Encoder
minified-generative-models
Bare-bones implementations of some generative models in Jax: diffusion, normalizing flows, consistency models, flow matching, (beta)-VAEs, etc
normalizing-flows
Understanding normalizing flows
VAE-Tensorflow
A Tensorflow implementation of a Variational Autoencoder for the deep learning course at the University of Southern California (USC).
smrt
Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.
VAE-for-Image-Generation
Implemented Variational Autoencoder generative model in Keras for image generation and its latent space visualization on MNIST and CIFAR10 datasets
DGAI
Learn Generative AI with PyTorch (Manning Publications, 2024)
MojiTalk
Code for "MojiTalk: Generating Emotional Responses at Scale" https://arxiv.org/abs/1711.04090
RecVAE
The official PyTorch implementation of the paper "RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback"
VGRNN
Variational Graph Recurrent Neural Networks - PyTorch
deepwriting
Code for `DeepWriting: Making Digital Ink Editable via Deep Generative Modeling` paper
precision-recall-distributions
Assessing Generative Models via Precision and Recall (official repository)
IMPLEMENTATION_Variational-Auto-Encoder
Simple implementation of Variational Autoencoder
calc2.0
CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure
Conditional_VAE
conditional variational autoencoder written in Keras [not actively maintained]
eccv16_attr2img
Torch Implemention of ECCV'16 paper: Attribute2Image
VAE_protein_function
Protein function prediction using a variational autoencoder
nichecompass
End-to-end analysis of spatial multi-omics data
vaegan
An implementation of VAEGAN (variational autoencoder + generative adversarial network).