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  • Search: subject:"Gaussian process regression"
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Year of publication
Subject
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Gaussian process regression 19 Artificial intelligence 9 Künstliche Intelligenz 9 Stochastic process 9 Stochastischer Prozess 9 Forecasting model 8 Prognoseverfahren 8 Gaussian process 7 Gauß-Prozess 7 Regression analysis 6 Regressionsanalyse 6 Theorie 6 Theory 6 Bayes-Statistik 5 Bayesian inference 5 Estimation theory 5 Machine learning 5 Schätztheorie 5 Immobilienpreis 4 Real estate price 4 machine learning 4 Bayesian optimization 3 China 3 Chinese market 3 Neural networks 3 Adam optimizer 2 Artificial neural networks 2 Cross-validation 2 Economic forecasting 2 Electric power industry 2 Elektrizitätswirtschaft 2 Gradient boosted decision trees 2 Identical parallel machine scheduling 2 Multiple-input multiple-output (MIMO) 2 Neuronale Netze 2 Operations research 2 Portfolio selection 2 Portfolio-Management 2 Tourism demand 2 Yield curve 2
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Online availability
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Free 19 CC license 11
Type of publication
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Article 16 Book / Working Paper 3
Type of publication (narrower categories)
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Article in journal 13 Aufsatz in Zeitschrift 13 Arbeitspapier 3 Article 3 Graue Literatur 3 Non-commercial literature 3 Working Paper 3
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Language
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English 19
Author
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Xu, Xiaojie 4 Jin, Bingzi 3 Claveria, Oscar 2 Gümbel, Sandrine 2 Monte, Enric 2 Nonaka, Hirofumi 2 Schmidt, Thorsten 2 Torra, Salvador 2 Yamashiro, Hirochika 2 Ajlouni, Sameh Asim 1 Alodat, Moh'd Taleb 1 Aslani, Babak 1 Avdoulas, Christos 1 Bekiros, Stelios 1 Das, Abhinav 1 Delucchi, Alessio 1 Filipović, Damir 1 Gaegauf, Luca 1 Giribone, Pier Giuseppe 1 Lahmiri, Salim 1 Londoño-Hernández, Sandra Milena 1 Manotas-Duque, Diego Fernando 1 Mohebbi, Shima 1 Oviedo-Gómez, Andrés 1 Pasricha, Puneet 1 Plašil, Miroslav 1 Scheidegger, Simon 1 Schlüter, Stephan 1 Trojani, Fabio 1 Zhang, Yun 1
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Published in...
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Decision analytics journal 2 International Journal of Energy Economics and Policy : IJEEP 2 International journal of empirical economics 2 Risks : open access journal 2 Asian journal of economics and banking : AJEB 1 International transactions in operational research : a journal of the International Federation of Operational Research Societies 1 Operations Research Perspectives 1 Operations research perspectives 1 Research and policy notes 1 Research paper series / Swiss Finance Institute 1 Risk management magazine 1 Risks 1 SERIEs - Journal of the Spanish Economic Association 1 SERIEs : Journal of the Spanish Economic Association 1 Swiss Finance Institute Research Paper 1
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Source
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ECONIS (ZBW) 16 EconStor 3
Showing 1 - 10 of 19
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Predicting wholesale edible oil prices through Gaussian process regressions tuned with Bayesian optimization and cross-validation
Jin, Bingzi; Xu, Xiaojie - In: Asian journal of economics and banking : AJEB 9 (2025) 1, pp. 64-82
Purpose - Developing price forecasts for various agricultural commodities has long been a significant undertaking for a variety of agricultural market players. The weekly wholesale price of edible oil in the Chinese market over a ten-year period, from January 1, 2010 to January 3, 2020, is the...
Persistent link: https://www.econbiz.de/10015339298
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Gaussian process regression with a hybrid risk measure for dynamic risk management in the electricity market
Das, Abhinav; Schlüter, Stephan - In: Risks : open access journal 13 (2025) 1, pp. 1-18
budget using the aforementioned measures to minimize the financial risk. To generate price predictions, a Gaussian process … regression model is used. The aim of this hybrid approach is to design a model that is easily understandable but allows for a …
Persistent link: https://www.econbiz.de/10015333597
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Forecasts of residential real estate price indices for ten major Chinese cities through Gaussian process regressions
Jin, Bingzi; Xu, Xiaojie - In: International journal of empirical economics 4 (2025) 1, pp. 1-24
Due to the rapid growth of the Chinese housing market over the past ten years, forecasting home prices has become a crucial issue for investors and authorities alike. In this research, utilising Bayesian optimisations and cross validation, we investigate Gaussian process regressions across...
Persistent link: https://www.econbiz.de/10015374007
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Machine learning-based scrap steel price forecasting for the Northeast Chinese market
Jin, Bingzi; Xu, Xiaojie - In: International journal of empirical economics 3 (2024) 4, pp. 1-21
account estimates for this significant commodity price measurement. In this instance, Gaussian process regression methods are …
Persistent link: https://www.econbiz.de/10015194297
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Learn to decompose multiobjective optimization models for large-scale networks
Aslani, Babak; Mohebbi, Shima - In: International transactions in operational research : a … 31 (2024) 2, pp. 949-978
Persistent link: https://www.econbiz.de/10014441148
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Modeling the interest rates term structure using Machine Learning : a Gaussian process regression approach
Delucchi, Alessio; Giribone, Pier Giuseppe - In: Risk management magazine 18 (2023) 3, pp. 16-35
The correct modeling of the interest rates term structure should definitely be considered an aspect of primary importance since the forward rates and the discount factors used in any financial and risk analysis are calculated from such structure. The turbulence of the markets in recent years,...
Persistent link: https://www.econbiz.de/10014491969
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A comparative assessment of machine learning methods for predicting housing prices using Bayesian optimization
Lahmiri, Salim; Bekiros, Stelios; Avdoulas, Christos - In: Decision analytics journal 6 (2023), pp. 1-8
regression, and Gaussian process regression. Bayesian optimization is implemented in a ten-fold cross-validation framework to …, followed by Gaussian process regression and support vector regression. In addition, all three aforementioned predictive systems …
Persistent link: https://www.econbiz.de/10014505865
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A Gaussian process regression machine learning model for forecasting retail property prices with Bayesian optimizations and cross-validation
Xu, Xiaojie; Zhang, Yun - In: Decision analytics journal 8 (2023), pp. 1-12
to 2021 through monthly data and Gaussian process regression models. We examine ten kernels, four basis functions, and …
Persistent link: https://www.econbiz.de/10014516551
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A comprehensive machine learning framework for dynamic portfolio choice with transaction costs
Gaegauf, Luca; Scheidegger, Simon; Trojani, Fabio - 2023
Persistent link: https://www.econbiz.de/10014483248
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Empirical Asset Pricing via Ensemble Gaussian Process Regression
Filipović, Damir; Pasricha, Puneet - 2022
We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected …
Persistent link: https://www.econbiz.de/10014236083
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