Creating and Training the LightGBM Autoencoder Model The LightGBM system does not have a built-in autoencoder class so one must be created using multiple regression modules.

The trained neural autoencoder is subjected to a sanity check by computing the MSE for the 40-item validation dataset. The MSE is 0.0017 which is very close to the MSE of the dataset being reduced, ...

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 ...

Researchers at the University of Texas at Austin produced data-driven and hybrid data-physics based DIP models to analyze stuck pipe incidents at the Frontier Observatory for ...

Researchers from Asan Medical Center, one of South Korea's largest hospitals, have developed a generative AI model that can ...