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

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

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 ...

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

A schematic of the stimuli seen by the mouse after vision onset in a virtual corridor rich with optic flow, created using a 3D animation software and used as the training dataset (Methods 4.1.4). The ...

WiMi Studies Quantum Hybrid Neural Network Model to Empower Intelligent Image Classification BEIJING, Jan. 15, 2026––WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global ...

Neural networks first treat sentences like puzzles solved by word order, but once they read enough, a tipping point sends them diving into word meaning instead—an abrupt “phase transition” reminiscent ...

As we've said before, gradient descent isn't the only neural network training method, but it is a powerful tool. Recurrent neural nets can even give gradient descent a boost by maintaining some memory ...

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