A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides. Hossein Abbasi, Mahdi Malekpour, Shahin Yaghoobi, Sina Abdous, Mohammad Hossein Rohban, ...

Specifically, we propose a Local Residual Quantized Variational AutoEncoder (Local RQ-VAE) to learn prototype vectors that represent the local details of high-quality images. Then we propose a ...

Convolutional neural network (CNN) has a powerful feature learning capability of automatic extraction of features and can categorize different scenes with high ... thereby proposing the ECA-DenseNet ...

Contribute to kk06112001/Variational-Autoencoders-VAE- development by creating an account on GitHub. Skip to content. Navigation Menu Toggle navigation. Sign in ... Features Train VAE, CVAE, and β-VAE ...

2.3.1 DenseNet. In this study, we make structural improvements based on the standard DenseNet framework. The traditional DenseNet usually contains an initial convolutional layer, multiple Dense blocks ...

Reproductive Medicine Center, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China; Objective: To evaluate the predictive performance of a convolutional neural network for analyzing ...

PyTorch implementation of Debiasing Variational Autoencoders (DB-VAE) for mitigating algorithmic bias in facial detection systems. - abasit/facial-detection-debiasing ...