In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...

Chinese researchers harness probabilistic updates on memristor hardware to slash AI training energy use by orders of magnitude, paving the way for ultra-efficient electronics.

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Researchers in China have developed an error-aware probabilistic update (EaPU) method that dramatically improves the ...

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

Introducing Annotatability—a powerful new framework to address a major challenge in biological research by examining how artificial neural networks learn to label genomic data. Genomic datasets often ...

Researchers are training neural networks to make decisions more like humans would. This science of human decision-making is only just being applied to machine learning, but developing a neural network ...

A simple and clear explanation of stochastic depth — a powerful regularization technique that improves deep neural network ...