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.

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 ...

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

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 ...

In this study, the authors recorded from the cerebellum while monkeys experienced an illusory perception of self-motion, and found that the neurons encoded the erroneous linear acceleration. Their ...

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 ...