Abstract: The widespread deployment of smart meters has created significant opportunities for applying artificial intelligence technologies to power system tasks. However, the high cost of data ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract ...

Integrating deep learning in optical microscopy enhances image analysis, overcoming traditional limitations and improving classification and segmentation tasks.

The Minnesota daycare infamously featured in a YouTuber's video on alleged fraud has closed, according to the state. The Quality Learning Center closed Tuesday, according to Minnesota Department of ...

1 School of Computer Engineering, Suzhou Polytechnic University, Suzhou, China 2 College of Science Mathematics and Technology, Wenzhou-Kean University, Wenzhou, China The proliferation of digital ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Abstract: Data-driven soft sensing models in industrial applications are often constrained by the scarcity of labeled data, which limits the effectiveness of supervised approaches. As a mainstream ...

The identification of wheat infections has always been a considerable problem in agricultural forecasting. This paper presents an automated classification framework for wheat illnesses utilising ...