Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, ...

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...

Abstract: Cognitive diagnosis (CD) utilizes students' existing studying records to estimate their mastery of unknown knowledge concepts, which is vital for evaluating their learning abilities.

BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...

ABSTRACT: An algorithm is being developed to conduct a computational experiment to study the dynamics of random processes in an asymmetric Markov chain with eight discrete states and continuous time.

Abstract: Port network information security has received extensive attention in recent years, in which the prediction of node links in the network is significant. A Port network is a dynamic network, ...

Positive predictive value was higher with MELD Graph compared with existing baseline algorithm. HealthDay News — A graph neural network using data from the Multicenter Epilepsy Lesion Detection (MELD) ...

Positive predictive value was higher with Multicenter Epilepsy Lesion Detection Graph compared with existing baseline algorithm. HealthDay News — A graph neural network using data from the Multicenter ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...