They're cheaper to train and getting smarter, so why bother with their little sibling SLMs (small language models)? For any ...

Topology detection (TD) in the context of power distribution networks (PDNs) is a fundamental requirement for a wide range of applications, such as fault localization and load management. PDNs suffer ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

ABSTRACT: Knowledge Graph (KG) and neural network (NN) based Question-answering (QA) systems have evolved into the realm of intelligent information retrieval as they have been able to reach a high ...

Secondly, the Double Hidden Layer Recurrent Neural Network (DHLRNN) is proposed to model the mapping relationships between variables in the power flow constraints, aiming to calculate the virtual ...

Results show that topology-sensitive characterizations of population codes are robust to noise and interindividual variability and maintain excellent sensitivity to the unique representational ...

Keywords: retinal images, artery/vein classification, vessel topology, convolutional neural networks, graph convolutional networks Citation: Mishra S, Wang YX, Wei CC, Chen DZ and Hu XS (2021) VTG-Net ...