IEEE

CVA 2 E: A Conditional Variational Autoencoder With an Adversarial Training Process for Hyperspectral Imagery Classification

Abstract: Deep generative models such as the generative adversarial network (GAN) and the variational autoencoder (VAE) have obtained increasing attention in a wide variety of applications.
IEEE

Automatically Inverse Design of FSSs by Conditional Variational Autoencoder and Equivalent Circuit Models With Large Language Models

Abstract: Recently, deep learning has attracted intensive attentions in electromagnetic society, especially for inverse problems. In this work, we propose two language-guided automatic design ...
GitHub

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

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 ...
GitHub

JunhanZhang0808/Conditional-VAE-Image-Generator

基于 条件变分自编码器 Conditional Variational Autoencoder, CVAE 的轻量级图像生成项目。 本项目可以使用一组图片进行训练 ...
Medical Device and Diagnostic Industry (MD+DI)

The AI Era: How Deep Learning is Overcoming Data Scarcity in Medical Imaging

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
C&EN

druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico

Article Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to ...
C&EN

Low Data Drug Discovery with One-Shot Learning

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