There are 1 repository under cvae topic.
Collection of generative models in Tensorflow
Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch
Tensorflow Implementation of Knowledge-Guided CVAE for dialog generation ACL 2017. It is released by Tiancheng Zhao (Tony) from Dialog Research Center, LTI, CMU
Tensorflow implementation of conditional variational auto-encoder for MNIST
pytorch implementation Variational Autoencoder and Conditional Variational Autoencoder
Learning informed sampling distributions and information gains for efficient exploration planning.
The official implementation of "Hierarchical Latent Structure for Multi-Modal Vehicle Trajectory Forecasting" presented in ECCV2022.
Code for our paper "VaPar Synth - A Variational Parametric Model for Audio Synthesis"
Official code for AAAI 2023 paper "Multi-stream Representation Learning for Pedestrian Trajectory Prediction"
Official project of DiverseSampling (ACMMM2022 Paper)
👾 Malware Classification using Deep Learning and Cuckoo Sandbox
Code for Generalization Guarantees for (Multi-Modal) Imitation Learning
PyTorch implementation of the conditional variational autoencoder (CVAE) from CodeSLAM
NCTU(NYCU) Deep Learning and Practice Spring 2021
PyTorch implementations of Variational Autoencoder and Conditional Variational Autoencoder
Implementation of the Conditional Variational Auto-Encoder (CVAE) in Tensorflow
An interactive demonstration of using a deep conditional variational autoencoder to generate synthetic MNIST style handwriting digit
The implementation of Gumbel softmax reparametrization trick for discrete VAE
Variational Auto Encoders (VAEs), Generative Adversarial Networks (GANs) and Generative Normalizing Flows (NFs) and are the most famous and powerful deep generative models.
Implementation of different autoencoders and their practical application
Implementation of CVAE. Trained CVAE on faces from UTKFace Dataset to produce synthetic faces with a given degree of happiness/smileyness.
cVAE, VQ-VAE, VQ-VAE2, cVAE-cGAN, PixelCNN and Gated PixelCNN in tensorflow 2.x and keras
a collection of variational autoencoders
A robust and unsupervised KPI anomaly detection algorithm based on conditional variational autoencoder
A robust and unsupervised KPI anomaly detection algorithm based on conditional variational autoencoder