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About this book

Introduction to UQ

Types of Uncertainty: Overview (DRAFT)
Fundamentals

Sources of Uncertainty

Overview of Sources of Uncertainty
Data-induced Uncertainty (DRAFT)
Method-induced Uncertainty
Implications (DRAFT)

Dealing with Uncertainty

Overview of Methods
Sensitvity Analysis [DRAFT]
- Linear Global Sensitivity via Regression and Correlation [DRAFT]
- Adjoint Sensitivity Analysis in UQ [DRAFT]
Monte-Carlo Method
- Multilevel Monte Carlo Method [Draft]
- Quasi-Monte Carlo Method
Uncertainty Quantification for a Dynamical Model
Bayesian Methods
Optimization Under Uncertainty
Surrogate Modelling Approach
Quantifying Uncertainty for Data Imputation Methods
Model Parameterization in Transdimensional Scheme (Draft)
Grid Node Based and Wavelet Based Parametrization (DRAFT)
Model Selection (Draft)
Diffusion Maps (Draft)
Data Assimilation [Draft]
- Kalman-Filter
- Ensemble Kalman Filter [DRAFT]

Toolboxes and Software

Overview Of Toolboxes And Software

Case Studies

Overview of Case Studies
UQ in Future Energy Systems
UQ in scRNA-Seq Experiments
- The Mathematical Perspective on Mapping Uncertainty in scRNA Experiments
- The Curse of Dimensionality in scRNA Data (draft)
UQ in Biodiversity Change
UQ in Earth Science Data
- Approaches to Handle Subjectivity
- Subjectivity in the Data Production - Geological Map Production as an Example
UQ in Biodegradable Magnesium-Based Implants
- Modelling The Degradation Of Biodegradable Implants
- Uncertainty Sources In Degradation Models
UQ in Surface Wave Tomography (Draft)
UQ in Earth System Sciences
UQ in Ocean Biogeochemical Models
UQ in Weather Prediction

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Ensemble Kalman Filter [DRAFT]

Contents

Author

Ensemble Kalman Filter [DRAFT]#

Author#

Nabir Mamnun, Maqsood Rajput

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Overview Of Toolboxes And Software

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By The Helmholtz UQ Community

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