Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

anthropomorphism: When humans tend to give nonhuman objects humanlike characteristics. In AI, this can include believing a ...

A practical guide to the four strategies of agentic adaptation, from "plug-and-play" components to full model retraining.

Open interest data suggests the advance is likely short-covering, rather than fresh longs entering the market.

A research team shows that phenomic prediction, which integrates full multispectral and thermal information rather than ...

ESG indices in emerging markets often lack long, transparent historical records, making them difficult to analyze with ...

From a governance perspective, the use of explainable AI is particularly significant. Infrastructure decisions involve public ...

By training statistical and machine-learning models to predict expert visual scores, the study demonstrates that phenomics can match or outperform ...

This important study combines optogenetic manipulations and wide-field imaging to show that the retrosplenial cortex controls behavioral responses to whisker deflection in a context-dependent manner.

Anyone preparing for quant interviews must develop depth across several skill areas and know how to apply theory in a ...

Abstract: Recently, deep learning has made brilliant achievements in wind turbine bearing fault diagnosis field. However, there are two problems that cannot be ignored: 1) the fault data are so scarce ...