This article introduces the autoencoder graph ensemble model (AEGEM), a novel ensemble-based framework designed to enhance performance in both endmember extraction and abundance estimation. In the ...

It uses an LSTM (Long Short-Term Memory) autoencoder model built with TensorFlow/Keras to learn normal patterns from your metrics and identify deviations. The system includes scripts for data ...

Liver disease modelling: This liver model reconstructs the liver periportal region architecture, is able to model aspects of cholestatic liver injury and biliary fibrosis, and can show how ...

Current AI algorithms employing attention mechanisms, such as transformers, perceiver and flamingo models, are inspired by the capabilities ... Adeel evaluated his adapted transformer architecture in ...

Moreover, most of the schemes decouple the model learning process, resulting in suboptimal performance. To tackle these challenges, in this paper, we propose a unified Unsupervised Gaussian Mixture ...