Additionally, combining these penalties enhances both reconstruction quality and the interpretability of latent features. The interpretable models identified genes such as LRP2 and ACE2 as highly ...

The traditional masked reconstruction model uses the autoencoder structure but cannot learn richer potential information and data structure. To this end, we propose to improve the latent space based ...

Biocatalysis has emerged as a green approach for efficient and sustainable production in various industries. In recent decades, numerous advancements in computational and predictive approaches, ...

However, most existing autoencoder-based methods discard the reconstruction of auxiliary information, which poses a huge challenge for better representation learning and model scalability.

Conventional reinforcement learning (RL) algorithms often necessitate millions of environment interactions to ascertain an efficacious policy. In stark contrast, humans, leveraging their curiosity ...

Image reconstruction-based methods with autoencoder have been widely used for unsupervised anomaly detection. By training the reconstruction on normal samples, ...