We consider a nonlinear function-on-function additive regression model with multiple functional predictors. The forms of the nonlinear functions are unspecified, and offer great flexibility to model ...

Computational methods for fitting nonlinear models have developed considerably in the last decade. Statistical use of these techniques has, as yet, lagged somewhat behind. The present paper gives a ...

Asymmetric interactions between different species of molecules have previously been demonstrated to result in self-organized ...

Getting an all-optical AI to handle non-linear math Instead of sensing photons and processing the results, why not process the photons?

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

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 ...

Recognizing the nonlinear behavior of the 12AX7 vacuum tube, used in audio and old op-amp applications, Dr. Dyer compares various models for fit to real-world device data.