The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

World models are the building blocks to the next era of physical AI -- and a future in which AI is more firmly rooted in our reality.

Abstract: In Coded Aperture Snapshot Spectral Imaging (CASSI) systems, model-based approaches highly rely on the handcrafted priors, while data-driven methods overlook the physical degradation process ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Natural gas purification plants are a critical part of the gas ...

Landslide susceptibility assessment is crucial to mitigate the severe impacts of landslides. Although Bayesian network (BN) has been widely used in landslide susceptibility assessment, no study has ...

Paper aims The aim of this study is to develop a bayesian network model for selecting maintenance strategies. Originality This model evaluates the consequences and complexity of breakdowns, but also ...

Experimental variogram modelling is an essential process in geostatistics. The use of artificial intelligence (AI) is a new and advanced way of automating experimental variogram modelling. One part of ...

Abstract: Over the last three decades, cellular network planning has evolved as a discipline in response to the ever-increasing complexity of mobile telephony. One of the key inputs to coverage ...