GitHub

An Intuitive Tutorial to Gaussian Processes Regression

@misc{wang2020intuitive, title={An Intuitive Tutorial to Gaussian Processes Regression}, author={Jie Wang}, year={2020}, eprint={2009.10862}, archivePrefix={arXiv}, primaryClass={stat.ML} } This ...
Visual Studio Magazine

Gaussian Process Regression Using the scikit Library

A regression problem is one where the goal is to predict a single numeric value. For example, you might want to predict the price of a house based on its square footage, age, number of bedrooms and ...
GitHub

Multi-output-Gaussian-Process

In multi-output regression (multi-target, multi-variate, or multi-response regression), we aim to predict multiple real valued output variables. One simple approach may be using combination of single ...
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 ...
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 ...
IEEE

Gaussian Process Regression-Based Traffic Prediction and Rate Coordination for Service Chain Congestion Mitigation

Abstract: With the rapid development of Internet technologies, the network traffic continues to grow exponentially, which leads to serious congestion and makes the service quality difficult to ...