The Martin-Hopkins equation to assess low-density lipoprotein (LDL) cholesterol levels in blood samples has been used by ...

As more and more Americans put their heads into the smiling noose of socialism, some of the politicians stringing them up are ...

We study inference via heteroskedasticity in linear models commonly used for macroeconomic policy analysis, where covariate endogeneity must often be addressed with limited time and data. Our ...

Revolut’s PRAGMA (PRe-trained Banking Foundation Model) is a family of encoder-style models scaling from 10 million to 1 billion parameters. This is the largest published encoder backbone for consumer ...

Underwater radiated noise (URN) from vessels is an anthropogenic stressor that negatively affects marine ecosystems. Accordingly, the ability to estimate URN levels is a critical component for ...

Meta released an AI model on Wednesday called Muse Spark, which marks its “first step” toward an “overhaul of [its] AI efforts.” Muse Spark is the inaugural model to come out of Meta Superintelligence ...

The era of size inclusivity is seemingly over. Our critic traces the shift and hopes designers might learn from it. By Vanessa Friedman I know models have always been skinny, but it seems to me they ...

The development of glmSMA represents a valuable advancement in spatial transcriptomics analysis, offering a mathematically robust regression-based approach that achieves higher-resolution mapping of ...

The Tesla Model Y’s midcycle refresh brought significant enough changes to earn it a spot in our 2026 SUV of the Year competition. The full list of updates is extensive, but the highlights matter.

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...