Calculations show that injecting randomness into a quantum neural network could help it determine properties of quantum ...

Engineers have uncovered an unexpected pattern in how neural networks -- the systems leading today's AI revolution -- learn, suggesting an answer to one of the most important unanswered questions in ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

The rise of artificial intelligence (AI) deep learning algorithms is helping to accelerate brain-computer interfaces (BCIs). Published in this month’s Nature Neuroscience is new research that shows ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

Artificial intelligence (AI) machine learning algorithms consist of neural networks that are inspired by the biological brain. However, today’s standard computing hardware architecture is not, hence ...

A technical paper titled “Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural networks: from Algorithms to Technology” was published by researchers at Intel Labs, University of ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

In a nutshell: Deep Learning Super Sampling (DLSS) technology popularized the use of neural networks to upscale and enhance real-time 3D graphics, delivering significant improvements in both ...