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C. Vuik

62 records found

High-dimensional data imputation is a critical challenge in semiconductor metrology, where secondary measurements are often purposely omitted to optimize throughput. This thesis examines the Missing By Design (MBD) framework—an industrially motivated scenario in which data are sy ...
Dutch pension funds are under the supervision by De Nederlandsche Bank (DNB) and they must adhere to the Financial Assessment Framework (FTK), which outlines the methods for calculating liabilities, buffer reserves, and risk factors. As part of the FTK, a feasibility test must be ...
This thesis addresses a timetabling problem known as Strategic Passenger-Oriented Timetabling (SPOT). SPOT is a timetabling problem that involves assigning departure and arrival times to train services. Unlike classical timetabling, which typically emphasizes infrastructural feas ...

Optimal Deposit Rate Modelling and Risk Assessment for Non-Maturing Deposits

An application to aggregate data of the Dutch banking sector

This thesis concerns the modelling, risk analysis and deposit rate optimization for Non-Maturing Deposits (NMDs), applied on aggregate data for the Dutch banking sector. The final NMD model consists of three parts, where there is a clear separation between the model for the term ...
This thesis aims to contribute to the understanding of how waves interact with soil. It is crucial for various applications in Civil Engineering to analyze the behaviour of soil and to understand the physics behind it. This master thesis contributes to this understanding via stud ...
This thesis addresses the challenge of segmenting ultra-high-resolution images. Limitations of current approaches to segment these are that either detailed spatial contextual information is lost or many redundant computations are necessary. To overcome these issues, we propose a ...

Causal Factor Investing

With an Application in the Corporate Bond Market

The rise of quantitative investment strategies has been driven by increased data availability and advancements in financial modeling. This thesis introduces Causal Factor Investing (CFI), a novel approach that integrates causality and machine learning to enhance the performance a ...
The topic of this thesis project is to use the particle-tracking framework to study salt intrusion.
This project was proposed by Deltares and is a small part of the SALTISolutions project, that attempts to build a digital twin model of the Rhine-Meuse Delta. From a mathematic ...
Financial markets continue to see an increase in the share of trades executed by algorithmic trading systems. A key component of an efficient algorithmic trading system is its ability to accurately estimate the probability an order will be executed: the fill probability. This the ...
Humans are efficient at moving due to their exceptional mastery of bipedal locomotion. Several models have been made that attempt to model the motion of the centre of mass with a spring-mass system with various degree of success. For example, a two dimensional model tracks the he ...
In many fields we are interested in inference for a complex stochastic process given limited observations regarding its state over time. This thesis therefore introduces an expectation propagation approach to backward filtering forward guiding for high-dimensional finite-state sp ...
The salinity profile in a coastal sea-river system is the result of balancing of salt transport due to mixing of the water by tides and the freshwater discharge from the river. When for example during times of drought freshwater discharge suddenly declines, the salinity in the ri ...
The computation of multivariate expectations is a common task in various fields related to probability theory. This thesis aims to develop a generic and efficient solver for multivariate expectation problems, with a focus on its application in the field of quantitative finance, s ...
In biology, phylogenetics is the study of the evolutionary history of and relations between e.g. species. Such data are often represented in trees. Remarkably, trees lack the representation of reticulation events, such as hybridization, while such events are believed to be import ...

CCS Reservoir Simulation using Graph Neural Networks

Building ML solutions for efficient CO2 subsurface modelling

Reducing cost and improving computability of reservoir simulation is an important goal in the process of enabling CCS (Carbon Capture \& Storage) as a large-scale technology for mitigating CO2 emissions. In terms of computation time data-driven approaches have potential to ou ...
Rendering accurate water reflections is crucial for achieving realism in computer graphics. Their integration with VR and AR technologies can further elevate experiences in sectors like education, engineering, and medicine. Even though various monoscopic reflection techniques exi ...
This thesis presents a comprehensive exploration of the rough Heston model as a means to enhance financial derivative pricing and calibration in the context of the complex behavior of market volatility. Recognizing the limitations of classical models, such as the Black-Scholes an ...
Barrier options, although highly liquid financial derivatives, present notable pricing challenges. In this thesis, we present a novel pricing approach for valuing continuously-monitored knock-out barrier options within the framework of stochastic volatility models.

The u ...
The right to use a certain amount of capacity in an electrical cable between two countries for the purpose of trading energy is an asset that can be bought. Each hour of capacity can be seen as a real spread option with the energy prices of each country being the underlying proce ...
Optimal control is a paradigm for solving optimization problems involving dynamical systems, which are to be controlled. It is able to solve fish harvesting problems, in which we want to optimize harvesting out-take by considering fishing as a control function that acts on the st ...