Moreover, we present an adaptive weighted Transformer, with the weights guided by a variational autoencoder (VAE), thereby enhancing the generalization and robustness of the model. The SGA and VAET ...

Introduction: Dementia, characterized by cognitive decline and impaired judgment, imposes a significant economic burden due to its rising prevalence and high diagnostic costs. Recent research has ...

Our model, known as the constrained subspace variational autoencoder (CS-VAE), successfully models distinct features of the behavioral videos across subjects, as well as continuously varying ...

Mental disorders such as schizophrenia have been challenging to characterize due in part to their heterogeneous presentation in individuals. Most studies have focused on identifying groups differences ...

2.3 Multi-Domain Variational Autoencoder In order to capture the combined anatomy and ECG data obtained from the preprocessing steps, we propose a multi-domain β -VAE (Higgins et al., 2017) ...

For both cases, the variational autoencoder with 4 hidden layers reached the lowest values. This indicates that 4-layer VAE is capable of generating protein conformations that are closer to the ...