In this work, I explore the creation of new methods that optimize simulations of the gravitational N-body problem. Specifically, I take advantage of the recent popularity of Machine Learning methods to find tools that can suit this problem.

Heeft jouw peuter of kleuter last van verlegen of angstig gedrag? Dan kan onze stapsgewijze (matched-care) behandeling, Brave Steps, jou misschien helpen. Bezoek de website voor meer informatie.

Promotores: T.H.W. Bäck, Y. Tan, Co-promotor: M.T.M. Emmerich

Promotor: H.W. Lenstra

Een stapsgewijze aanpak voor het opbouwen van zelfvertrouwen bij jonge kinderen die angstig zijn.

Promotor: Prof.dr. P. Stevenhagen

The complexity of an intelligence problem determines to a great extent the certainty that can be provided by intelligence and security services.

Heterogeneous catalysis is essential to many industrial applications. These catalysts are often comprised of supported nanoparticles, which contain various different surface sites.

Inverse problems are problems where we want to estimate the values of certain parameters of a system given observations of the system. Such problems occur in several areas of science and engineering. Inverse problems are often ill-posed, which means that the observations of the system do not uniquely…

Promotor: W.T. de Groot

Promotores: P. Stevenhagen, A. Enge Co-Promotor: T.C. Streng

This study tests whether behavioural problems at a young age are related to early reading and mathematics development.

In this thesis we investigate cosmology and the large scale structure of the Universe using cosmological simulations.

Latent variable modeling of students' solution strategies and performance

Promotor: S.M. Verduyn Lunel, Co-promotor: O.W. van Gaans

The increasing competition in the automotive industry requires the tailored, swift development of technologically sophisticated vehicles. Therefore, the computationally expensive state-of-the-art simulation technologies are combined with optimization algorithms. An example of a real-world optimization…

Uncertainty and noise are frequently-encountered obstacles in real-world applications of numerical optimization. The practice of optimization that deals with uncertainties and noise is commonly referred to as robust optimization.

Promotores: Prof.dr. H.S. Overkleeft, Prof.dr. G.A. van der Marel

Students with learning problems experience difficulties in reading, writing, and content-area learning into and throughout their secondary-school years

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The class-imbalance problem is a challenging classification task and is frequently encountered in real-world applications. Various techniques have been developed to improve the imbalanced classification performance theoretically and practically.

Schuurman onderzoekt hoe Rusland zijn geheime operaties tegen Europese landen laat escaleren.

In this thesis, deep learning is studied from a statistical perspective. Convergence rates for the worst case risk bounds of neural network estimators are obtained in the classification, density estimation and linear regression model.

A common method to solve expensive function evaluation problem is using Bayesian Global Optimization, instead of Evolutionary Algorithms.

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Polymyxins are clinically used antibiotics, discovered in mid-20th century. Once abandoned due to excessive nephrotoxicity, they are now used increasingly to address infections caused by multi-drug resistant Gram-negative bacteria.In this thesis, we describe the development and synthesis of analogues…

The Copenhagen interpretation of quantum mechanics states that a measurement collapses a wavefunction onto an eigenstate of the corresponding measurement operator.

Dit onderzoek presenteert een vijfstappenplan voor de ontwikkeling van een effectieve gedragsgerichte cyberveiligheidsstrategie.

Promotor: K.J. Batenburg

Promotores: H.W. Lenstra, K. Belabas (University of Bordeaux)

In dit artikel heeft Lianne Visser bijgedragen aan het begrip rondom samenwerkend bestuur als uitdagende aanpak voor hardnekkige problemen.

In this dissertation, we work towards an experiment in which we aim to bring a micrometer sized magnet at the tip of a soft cantilever into a superposition.

Wat zijn de beste werkwijzen om studenten te leren omgaan met complexe problemen?

Statistical distributions in LCA and converting between different representations of these distributions.

Time-series forecasting through modelling sequences of temporally dependent observations has many industrial and scientific applications. While machine learning models have been widely used to create time-series forecasting models, creating efficient and performant time-series forecasting models is…

This dissertation studies the Asymptotics of Bayesian nonparametric inference for Gaussian linear models.

Promotor: M.T.M. Koper, Co-promotor: J.B.F. Juurlink

The research presented in this thesis makes use of small molecules (as H2 , D2 and O2 ) on well-defined single crystal surfaces (flat Pt(111), flat Cu(211) and curved Pt(111)) to elucidate the role of surface structure and degrees of freedom in the reactant in specific surface reactions.

This dissertation focuses on developing new mathematical and statistical methods to properly represent time-varying covariates and model them within the context of time-to-event analysis.

The thesis is part of a bigger project, the HEPGAME (High Energy Physics Game). The main objective for HEPGAME is the utilization of AI solutions, particularly by using MCTS for simplification of HEP calculations.

Hydrogen fuel cells are expected to be pivotal in the energetic transition towards renewable energy sources such as solar and wind power. However, their industrial scalability is severely hindered by the high cost and degradation rate of platinum catalysts, one of their key components. Addressing this…

The global agri-food system plays a critical role in food security and environmental issues.

Promotor: K.J. Batenburg, Co-promotor: A.W. van der Vaart, B. de Smit

Promotores: K.J. Batenburg, B. Koren

Promotor: Prof.dr.ir. E. Deprettere

Why do sexual violence policies still fail to systematically address men and masculinities, when the need for cultural change among men has been central in public debates since #MeToo?

In this dissertation non-parametric Bayesian methods are used in the application of robotic vision.