AI in Computer-Aided Synthesis Planning Market reached USD 2.13 bn in 2024 and is expected to grow rapidly to USD 68.06 bn by ...

BiGRU, a deep learning model that enhances data recovery in structural health monitoring, ensuring the reliability of bridge ...

Artificial intelligence and deep learning have revolutionized the field of neural data analysis in recent years. The explosion of complex, high-dimensional ...

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...

Abstract: In recent years, Graph Neural Networks (GNNs) have demonstrated strong adaptability to various real-world challenges, with architectures such as Vision GNN (ViG) achieving state-of-the-art ...

San Francisco-based CoreStory is working to speed up the software modernization workflow. The company has developed an ...

The second system, called MAGNET-AD, employs a graph neural network to detect Alzheimer’s disease before symptoms appear. It predicts both a patient’s cognitive performance score (PACC) and the time ...

Traditional experimental methods for evaluating gas adsorption performance of metal–organic frameworks (MOFs) are costly and time-consuming, while ...

Abstract: Graph neural networks (GNNs) have shown promise in graph classification tasks, but they struggle to identify out-of-distribution (OOD) graphs often encountered in real-world scenarios, ...

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...

Evaluating the advantages and potential drawbacks of shielding as a method for safe RL. Bettina Könighofer is an assistant ...

For years, we have watched large language models (LLMs) capture our imagination. ChatGPT writes emails, Gemini provides answers, and Llama powers a wide range of applications. But behind their ...