In model-based fault diagnosis, the ability to identify the key observational data that leads to system abnormalities is highly valuable. This paper introduces a framework and algorithm for identifying key observational data. The framework determines which observations are crucial for diagnosis by abstracting the raw observational data into “sub-ob...

With the widespread application of graph-structured data in various fields, Graph Neural Networks (GNNs) have attracted significant attention as a powerful tool for analyzing graph data. However, existing GNNs primarily rely on neighborhood node similarity information when learning node representations, overlooking the potential of node differences...

Circuit Mechanisms of Hue Selectivity in the Fruit Fly Visual System Color perception is a key aspect of visual experience, playing an important role in the interaction between organisms and their environment. In primates and other animals with three types of photoreceptor cells, neurons in the visual cortex have been found to selectively respond t...

Background Introduction: Large-scale neural recording data can typically be described by patterns of co-activated neurons. However, the view of constraining neural activity variability to a fixed low-dimensional subspace may overlook higher-dimensional structures, such as fixed neural sequences or slowly evolving latent spaces. This study argues th...