Whenever we mull over what film to watch on Netflix, or deliberate between different products on an e-commerce platform, the ...

Without proper planning, the scaling process can feel like patching a leaky pipe—constantly reacting to problems instead of ...

Supported by the OECD, a total of 23 schools from seven countries have joined the network. Read more at straitstimes.com.

This study proposes a comprehensive strategy to optimize the operation of real-world gas pipeline networks and support decision-making. The goal is to improve environmental sustainability by ...

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 ...

A new product will establish the graph-based industry standard for secure, orchestrated access to APIs in the age of AI… so says Apollo GraphQL, a graph-based API orchestration company.

Graph neural networks (GNNs), an emerging class of machine learning models for graphs, have gained popularity for their superior performance in various graph analytical tasks. Mini-batch training is ...

This is something i would like to see. a network graph of docker image. the idea would be to create a "node" by the name of the network and connect container connected to it. this could also incorp ...

A graph neural network using data from the Multicenter Epilepsy Lesion Detection (MELD) Project (MELD Graph) can detect epileptogenic focal cortical dysplasia (FCD) on magnetic resonance imaging ...

It was characterized by implementing three modules of graph convolutional network (GCN), spatial convolution and long short-term memory (LSTM) to effectively extract time-frequency-spatial features ...

In recent years, superpixel-based graph convolutional networks (GCNs) have drawn increasing attention within the hyperspectral image (HSI) classification community. Due to the high-dimensional ...