Detail page

Knowledge Web

Person

Hu Zhao

Geowissenschaftler

Name	Hu Zhao
Place	Anhui China Deutschland
Academic degree	Dr.-Ing., M.Eng.
Profession	Geowissenschaftler (characteristic profession)
Variant	Zhao Hu Zhao Hu
Further information	Dissertation an der Rheinisch-Westfälischen Technischen Hochschule Aachen, Fakultät für Georessourcen und Materialtechnik, 2021
Source	Dissertation
Record type	Person
GND-Identifier	1248263650
Record ID	1248263650
Involved in show all Bayesian active learning for parameter calibration of landslide run-out models Bayesian active learning for parameter calibration of landslide run-out models Open AR-Sandbox : A haptic interface for geoscience education and outreach Physics-informed machine learning to model rapid complex geohazards Emulator-based global sensitivity analysis for flow-like landslide run-out models Emulation techniques for rapid flow-like geohazards : a case study-based performance analysis Emulator-based global sensitivity analysis for flow-like landslide run-out models Gaussian processes for sensitivity analysis, Bayesian inference, and uncertainty quantification in landslide research Topographic uncertainty quantification for flow-like landslide models via stochastic simulations Topographic uncertainty in mass flow simulations - preliminary results

Please note

The beta version does not yet contain all functions and information of the DNB portal catalogue. If you are missing information or want to order a medium, please visit the page in the DNB portal catalogue via the following link:

Katalog der Deutschen Nationalbibliothek

Hu Zhao

Bayesian active learning for parameter calibration of landslide run-out models

Bayesian active learning for parameter calibration of landslide run-out models

Open AR-Sandbox : A haptic interface for geoscience education and outreach

Physics-informed machine learning to model rapid complex geohazards

Emulator-based global sensitivity analysis for flow-like landslide run-out models

Emulation techniques for rapid flow-like geohazards : a case study-based performance analysis

Emulator-based global sensitivity analysis for flow-like landslide run-out models

Gaussian processes for sensitivity analysis, Bayesian inference, and uncertainty quantification in landslide research

Topographic uncertainty quantification for flow-like landslide models via stochastic simulations

Topographic uncertainty in mass flow simulations - preliminary results