GitHub

saeedmohseni97/gpr-robotic-arm

This project explores Gaussian Process Regression (GPR)—a non-parametric Bayesian approach to regression—applied to a robotic arm modeling problem with an 8-dimensional input space. Through simulation ...
Risk

Gaussian process regression for derivative portfolio modeling and application to credit valuation adjustment computations

Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all trades between each counterparty under both market and credit risk. We present a ...
Microsoft

Learning Gaussian Process Kernels via Hierarchical Bayes

We present a novel method for learning with Gaussian process regression in a hierarchical Bayesian framework. In a first step, kernel matrices on a fixed set of input points are learned from data ...
IEEE

Implementation of a Real-Time Force Estimation System Based on sEMG Signals and Gaussian Process Regression: Human–Robot Interaction in Rehabilitation

Abstract: Human force estimation has numerous applications, including biomedical models, rehabilitation, biomechanical system control, and human-machine interfaces. To enable such applications, it is ...
IEEE

Adaptive Optimizable Gaussian Process Regression Linear Least Squares Regression Filtering Method for SEM Images

Abstract: Scanning Electron Microscopy (SEM) images often suffer from noise contamination, which degrades image quality and affects further analysis. This research presents a complete approach to ...
JSTOR Daily

Posterior Consistency of Gaussian Process Prior for Nonparametric Binary Regression

Consider binary observations whose response probability is an unknown smooth function of a set of covariates. Suppose that a prior on the response probability function is induced by a Gaussian process ...