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

We demonstrate the implementation of a variety of non-linear models that are more appropriate for modeling plant growth than are the traditional, linear, models.Ecological inference is frequently ...

Generalized linear models (GLMs) are widely used for data analysis; however, their likelihood estimators can be sensitive to outliers. We propose new statistical models that allow robust inferences ...

Lawrence J. Christiano, Solving the Stochastic Growth Model by Linear-Quadratic Approximation and by Value-Function Iteration, Journal of Business & Economic Statistics, Vol. 8, No. 1 (Jan., 1990), pp ...

Deforming them is tricky and the deformations must be integrated into the actual model. That is, without something like a non-linear deformation space, as this paper talks about.

However, AI models are often used to find intricate patterns in data where the output is not always proportional to the input. For this, you also need non-linear thresholding functions that adjust ...

In this chapter, we propose a log-linear model for the biases observed when analyzing model communities data. Our model expands the recent work from McLaren, Willis and Callahan (MWC) [eLife, 8:e46923 ...

Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this ...