In the GPR modeling approach, this regression function, f(x), is assumed to follow a Gaussian process (GP), which means the function f(x) is related to the independent vector x via a Gaussian distribution:(5)f(x
In the spatial domain, a 2D Gabor filter is a Gaussian kernel function. The impulse response of these filters is created by convoluting a Gaussian function g(x, y) = 1 2π σ 2 e − x2 +y2 2σ 2 +2π jF (x cos θ +y sin θ ) (1) where θ represents the orientation, ...
FORCE uses an ensemble of Gaussian convolution filters with a radial basis function (RBF) kernel weighted by data availability to generate smooth temporal profiles (Schwieder et al., 2016, Frantz, 2019). In this way, a smooth time series consisting of estimated observations at regular intervals ...
deobliquing; motion correction; transformation to the spatially normalized anatomic image; regression of the mean timecourse and temporal derivative of the WM and CSF masks as well as a 24-parameter motion model41,42; spatial smoothing (6-mm FWHM Gaussian kernel); and scaling to percent signal...
In contrast, Bayesian optimization, makes the assumption that the unknown function belongs to a known model class (typically a class of smooth functions), the most common being a Gaussian process (GP) generated using a Gaussian or Matérn kernel (Stein 2012). We review LO and BO in Sect. ...
(TableS1). We used two different machine learning models and compared their performance: gaussian process regression (GPR)27and random forest regressor (RFR)28. GPR and RFR are one of the most popular machine learning models, which have been used for study such as antibody engineering field29,...
Since is normalized, each position corresponds to a Gaussian kernel function or adaptive geometric Gaussian kernel function with a sum of 1. By summing the pixels of the density function F(x, y), the number of people can be obtained. However, due to the addition operation, false peaks may...
To improve convergence, we blur the frame by convolution Gσ ∗ I with the Gaussian kernel Gσ before optimization. Blurring effectively suppresses noise and, along with it, high-frequency details. It has a positive impact on the smooth- ness of the energy function, but may cause a slight...
The weight value is mainly defined by the similarity between the atlas images and the target image; examples include the absolute value of the intensity difference11, the Gaussian function of the intensity difference12, and the local mutual information13. CoupeK et al.14 proposed a hippocampal ...
The UCB acquisition function, for a Gaussian Process posterior with mean function, [Math Processing Error], and variance function [Math Processing Error] is given by: (7)[Math Processing Error]In this equation, [Math Processing Error] represents our belief of how the function looks like. We ...