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 ...

We develop locally D-optimal designs for nonlinear models when the variance of the response is a function of its mean. Using the two-parameter Michaelis-Menten model as an example, we show that the ...

This article was originally published on Built In by Eric Kleppen. Variance is a powerful statistic used in data analysis and machine learning. It is one of the four main measures of variability along ...

Where can I find the random parameter matrix in MLwiN? How do I use this to work out the residual ('unexplained') variance at each level? Variances and covariances are stored in column c1096. (See ...

Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...