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.

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

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 ...

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 ...

Catalog : MATH.5910 Linear Statistics Modeling and Regression (Formerly 92.591) Id: 008463 Credits Min: 3 Credits Max: 3 Description Model building via linear regression models. Method of least ...

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 ...

Nicole Malfait, James O. Ramsay, The Historical Functional Linear Model, The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 31, No. 2 (Jun ...

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 ...