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

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

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

Promotor: H.W. Lenstra

Promotor: Prof.dr. P. Stevenhagen

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…

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

Deze masterspecialisatie leert je veelvoorkomende leerproblemen herkennen en behandelen.

Latent variable modeling of students' solution strategies and performance

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

Promotor: W.T. de Groot

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

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

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

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 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.

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

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

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.

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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.

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

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

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

Promotor: K.J. Batenburg

Materials balances have been used in the recent past for the analysis of substance oriented environmental problems and the formulation of measures for environmental policy. In this study an integrated tool, based on the materials balance principle, has been developed for the analysis of both environmental…

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

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

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…

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

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.

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.

One of the major limitations in culturing complex tissues or organs is the lack of vascularization in the cultured tissue. Development of a functional capillary bed could overcome this problem.

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

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

Promotor: Prof.dr.ir. E. Deprettere

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

Given the accelerating appearance of antimicrobial resistance, there is an urgent need for more fundamental research into novel antibiotic strategies. The work in this thesis helps to address this global problem by developing new antibiotic compounds, inspired by the antibacterial mechanisms of the…

Promotores: Prof.dr. J. Aarts, Prof.dr. J.M. van Ruitenbeek

Overall dispersion in LCA as result of inherent uncertainties, spread and unrepresentativeness.

The parabolic Anderson model (PAM), which is the Cauchy problem for the heat equation with random potential. The PAM is a mathematical model that describes how mass (i.e. matter or energy) flows in a medium in the presence of a field of sources and sinks.

Promotores: K.J. Batenburg, B. Koren

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

Promoter: Ed F. Deprettere, Co-promoter: Todor P. Stefanov

Promotor: Prof.dr. A. Doelman, Co-promotor: V. Rottschäfer