Abstract: Nonlinear models with a linear-in-coefficients property, i.e., the property that the model output is linear with respect to model coefficients, are highly valuable for behavioral modeling of ...

A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...

NTT Research, Inc., a division of NTT (TYO: 9432), announced that its Physics and Informatics (PHI) Lab, working with Cornell University and Stanford University, has developed the world's first ...

Director of National Intelligence Tulsi Gabbard told Megyn Kelly during an interview this week that there is an ongoing investigation to prove the role U.S.-funded research at the Wuhan Institute of ...

STG-DMD (Sparse-Coded Time-Delay Graph Dynamic Mode Decomposition) is a data-driven framework for modeling nonlinear dynamics on graph structures. It integrates: StgDmd/ ├── code/ │ ├── artificial/ │ ...

The solution of the nonlinear differential equation Y″ = F(x, Y, Y′) with two-point boundary conditions is approximated by a quintic or cubic spline function y(x ...

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 ...

Objective: This study aims to explore the association between alcohol intake and cognitive function in elderly Americans, including potential nonlinear relationships and interactions across different ...

This paper introduces a novel hierarchical graph-based long short-term memory network designed for predicting the nonlinear seismic responses of building structures. We represent buildings as graphs ...