Nonlinear mixed effects models (NLMMs) and self-modeling nonlinear regression (SEMOR) models are often used to fit repeated measures data. They use a common function shared by all subjects to model ...

This is a preview. Log in through your library . Abstract Multinomial logit models, especially those calibrated on scanner data, often use explanatory variables that are nonlinear functions of the ...

Artificial intelligence models have improved weather forecasting, but their inner workings are largely opaque. A new approach ...

Long-term weather forecasting is a difficult task, partly because weather systems are inherently chaotic. Though mathematical ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Highly reduced order models with nonlinear contact – extremely efficient computation. Modeled as linear components interconnected with highly reduced-order components. 1-linear reduced model, ...

In this important work, the authors present a new transformer-based neural network designed to isolate and quantify higher-order epistasis in protein sequences. They provide solid evidence that higher ...

A standard digital camera used in a car for stuff like emergency braking has a perceptual latency of a hair above 20 milliseconds. That’s just the time needed for a camera to transform the photons ...

Advanced space travel relies on a fundamental understanding of the restricted three-body problem (RTBP), in which one of the ...