Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...
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VFF-Net algorithm provides promising alternative to backpropagation for AI training
Deep neural networks (DNNs), which power modern artificial intelligence (AI) models, are machine learning systems that learn ...
What are convolutional neural networks in deep learning? Convolutional neural networks are used in computer vision tasks, which employ convolutional layers to extract features from input data.
Spiking Neural Networks (SNNs) are a cutting-edge approach to artificial intelligence, designed to emulate the brain's architecture and functionality. Their ...
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Brain Cells on a Computer Chip Offer Advanced Medical Treatments and Use Less Energy
Learn more about the new biological computer that fuses brain cells and computer chips — and uses far less energy.
An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...
Ryan Lee has received funding from the Air Force Office of Science Research . The new material is a type of architected material, which gets its properties mainly from the geometry and specific traits ...
Pancreatic neuroendocrine neoplasms (PNENs) are a rare form of cancer that affects hormone-producing cells in the pancreas.
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