Search Results - subject:"Gaussian Process Regression"

Designing macro-financial scenarios: the new CNB framework and satellite models for property prices and credit

Plašil, Miroslav - 2021

Persistent link: https://www.econbiz.de/10012792207

A recommending system for mobile games using the dynamic nonparametric model

Bae, Joonho; Park, Jinkyoo; Choi, Jeonghye; Soh, Seung Bum - In: Journal of business research : JBR 167 (2023), pp. 1-12

Persistent link: https://www.econbiz.de/10014383056

Physics-informed Gaussian process regression for states estimation and forecasting in power grids

Tartakovsky, Alexandre M.; Ma, Tong; Barajas-Solano, … - In: International journal of forecasting 39 (2023) 2, pp. 967-980

Persistent link: https://www.econbiz.de/10014465184

The valuation of corporations : a derivative pricing perspective

Madan, Dilip B.; Wang, King - In: Annals of finance 19 (2023) 1, pp. 1-21

Persistent link: https://www.econbiz.de/10014253867

Machine learning for multiple yield curve markets: Fast calibration in the Gaussian affine framework

Gümbel, Sandrine; Schmidt, Thorsten - In: Risks 8 (2020) 2, pp. 1-18

and many challenges for the multi-curve markets in a Vasiécek framework. The Gaussian process regression is implemented … process regression, a machine learning methodology having many similarities with extended Kálmán filtering, which has been … to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian …

Persistent link: https://www.econbiz.de/10013200584

Machine learning for multiple yield curve markets : fast calibration in the Gaussian affine framework

Gümbel, Sandrine; Schmidt, Thorsten - In: Risks : open access journal 8 (2020) 2/50, pp. 1-18

and many challenges for the multi-curve markets in a Vasiček framework. The Gaussian process regression is implemented … process regression, a machine learning methodology having many similarities with extended Kálmán filtering, which has been … to study the chances and challenges of the application of machine learning techniques for this. We employ Gaussian …

Persistent link: https://www.econbiz.de/10012292851

Moving average options : machine learning and Gauss-Hermite quadrature for a double non-Markovian problem

Goudenège, Ludovic; Molent, Andrea; Zanette, Antonino - In: European journal of operational research : EJOR 303 (2022) 2, pp. 958-974

Persistent link: https://www.econbiz.de/10013364051

Hierarchical Bayesian Gaussian process regression model for loss reserving using combinations of squared exponential kernels

Ang, Zi Qing; Lee, See Keong - In: Insurance / Mathematics & economics 105 (2022), pp. 54-63

Persistent link: https://www.econbiz.de/10013348919

Bayesian optimization allowing for common random numbers

Pearce, Michael Arthur Leopold; Poloczek, Matthias; … - In: Operations research 70 (2022) 6, pp. 3457-3472

Persistent link: https://www.econbiz.de/10014307875

An integrated data mining framework for organizational resilience assessment and quality management optimization in trauma centers

Tavana, Madjid; Nazari-Shirkouhi, Salman; Mashayekhi, Amir - In: Operations research forum 3 (2022) 1, pp. 1-33

Persistent link: https://www.econbiz.de/10013173161