BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs ...

Density functional theory is a widely used computer-based quantum mechanical method for calculating properties of atoms, ...

The rise of artificial intelligence (AI) deep learning ... Supervised machine learning, or supervised learning for short, includes classification algorithms such as neural networks, gradient ...

EPFL researchers have developed a groundbreaking algorithm that efficiently trains analog neural networks, offering an energy-efficient alternative to traditional digital networks. This method, which ...

enabling the development of more efficient alternatives to power-hungry deep learning hardware. EPFL researchers have developed an algorithm to train an analog neural network just as accurately as ...

Neural networks requires less time than deep learning Neural networks, while powerful in synthesizing AI algorithms, typically require less resources. In contrast, as deep learning platforms take ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep ... neural networks, typically use some form of gradient descent algorithm to ...

Hinton's motivation for the algorithm ... learning in cortex and as a way of making use of very low-power analog hardware without resorting to reinforcement learning. Although artificial neural ...

In his NeurIPS keynote speech last week, Hinton offered his thoughts on the future of machine learning — focusing on what he has dubbed the “Forward-Forward” (FF) algorithm. Deep neural networks that ...