GitHub

ti2ni1m/Image-Generation-with-Conditional-Variational-Autoencoder-C-VAE-and-Conditional-GAN ...

In this project, I aim to create a set of images of Kuzushiji Japanese characters via the Kuzushiji-49 dataset using 2 graphical models which are Conditional-Variational Autoencoder(C-VAE), and ...
GitHub

VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to ...

In our recent paper, we propose VITS: Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speech. Several recent end-to-end text-to-speech (TTS) models enabling single ...
IEEE

Conditional Generative Flow-Induced Variational Autoencoder for Plasma Instances Augmentation

Abstract: In this article, we propose a novel conditional generative flow-induced variational autoencoder (CGlow-VAE) model to address the critical challenge of the small sample issue in plasma ...
Europe PMC

ICVAE: Interpretable Conditional Variational Autoencoder for De Novo Molecular Design.

Recent studies have demonstrated that machine learning-based generative models can create novel molecules with desirable properties. Among them, Conditional Variational Autoencoder (CVAE) is a ...
Frontiers

Deep conditional generative model for personalization of 12-lead electrocardiograms and ...

Background: 12-lead electrocardiograms (ECGs) are a cornerstone for diagnosing and monitoring cardiovascular diseases (CVDs). They play a key role in detecting abnormalities such as arrhythmias and ...