Inside each cell of the human body are proteins that control which genes are expressed at the right place and time. However, ...

AUTOVC is a voice-conversion method that performs self-reconstruction using an autoencoder structure for zero-shot voice conversion. AUTOVC has the advantage of being easy and simple to learn because ...

When people think of DNA, they usually think of genes, the parts that code for proteins and drive inherited traits. But there ...

A transfer-learned hierarchical variational autoencoder model for computational design of anticancer peptides.. If you have the appropriate software installed, you can download article citation data ...

Reconstruction loss and KL divergence were used to detect abnormal behavior, and Particle Swarm Optimization (PSO) was applied to optimize the deep autoencoder structure. Yao et al. [51] proposed ...

AETHER-Research is a research initiative focused on the fundamental principles and diverse applications of AutoEncoders (AEs). We investigate the theoretical underpinnings of AE models and develop ...

The specific structure of the convolutional autoencoder in this paper is shown in Figure 1: the encoder consists of two convolutional layers, a batch layer, and a Leaky ReLU activation function, while ...

A new research by Google DeepMind shows how sparse autoencoders (SAEs) with special JumpReLU activation can help interpret LLMs.