The research on intelligent fault diagnosis has yielded remarkable achievements based on
artificial intelligence-related technologies. In engineering scenarios, machines usually work …

Recent advances in Internet of Things (IoT) technologies and the reduction in the cost of
sensors have encouraged the development of smart environments, such as smart homes …

The effectiveness of traditional supervised fault diagnosis methods for wind turbine
gearboxes typically depends on accurate labels, which are time-consuming and challenging …

Motivation Protein representation learning methods have shown great potential to many
downstream tasks in biological applications. A few recent studies have demonstrated that …

Meta-learning has gained wide popularity as a training framework that is more data-efficient
than traditional machine learning methods. However, its generalization ability in complex …

Satellite image time series (SITS) is a sequence of satellite images that record a given area
at several consecutive times. The aim of such sequences is to use not only spatial …

Meta-learning is increasingly used to support the recommendation of machine learning
algorithms and their configurations. These recommendations are made based on meta-data …

Radar target detection (RTD) is a fundamental but important process of the radar system,
which is designed to differentiate and measure targets from a complex background. Deep …

Radar automatic target recognition (RATR) technology is fundamental but complicated
system engineering that combines sensor, target, environment, and signal processing …

In this paper we investigate the active inference framework as a means to enable
autonomous behavior in artificial agents. Active inference is a theoretical framework …