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

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 ...

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 ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

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 ...

For all their brilliance, artificial neural networks remain as inscrutable as ever. As these networks get bigger, their abilities explode, but deciphering their inner workings has always been near ...