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 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 ...
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.
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 ...
Deep Learning with Yacine on MSN
Stochastic depth for neural networks – explained clearly
A simple and clear explanation of stochastic depth — a powerful regularization technique that improves deep neural network ...
Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...
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 ...
Researchers have devised a way to make computer vision systems more efficient by building networks out of computer chips’ logic gates. Networks programmed directly into computer chip hardware can ...
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