We explored how to morphologically classify well-resolved jetted radio-loud active galactic nuclei (RLAGN) in the LOw Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) using machine learning.

Understanding how data derived from wearable technology can be used to identify effective changes in behaviour that are likely to result in health improvements

With the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media.

In this thesis, we have studied cell images from two types of cells, including pollen grains and the immune cells, neutrophils. These images are captured using a bright field microscope and a confocal microscope.

With textnets it is possible to visualize and analyze textual data in novel ways.

The Explainatory Data Analysis group develops algorithms and theory that enable domain experts to explain data by finding interpretable patterns and models.

In this dissertation, we study partition-based models that can be used both for interpretable predictive modeling and for understanding data via interpretable patterns.

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Promotor: Prof.dr. J.N. Kok, Co-promotor: F.J. Verbeek

Are you thinking about studying Cultural Analysis: Literature and Theory? Learn more and watch the introduction video.

Explore "Analysis of Repeated Measurements" at Boerhaave Nascholing. Learn statistical methods for correlated data in time. Read more here.

In this publication, Prof. Tahir Abbas, Inés Bolaños Somoano, Joana Cook, Isabelle Frens, Graig R. Klein and Richard McNeil-Willson look into the manifesto that was linked to the Buffalo attack in order to better understand the broader context and specific factors that motivated the perpetrator.

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Overlevingsanalyse is een onderzoeksgebied dat zich richt op het bestuderen van de tijd tot het optreden van een specifieke uitkomst.

Predictive maintenance (PdM) is a maintenance policy that uses the past, current, and prognosticated health condition of an asset to predict when timely maintenance should occur.

The research of our group is centered around dynamical systems, functional analysis and their interplay.

Radiography is an important technique to inspect objects, with applications in airports and hospitals. X-ray imaging is also essential in industry, for instance in food safety checks for the presence of foreign objects.

The research of the Applied Mathematics cluster is concerned with such diverse topics as dynamical systems, representation theory, differential equations and pattern recognition.

This thesis investigates the application of deep learning techniques in image analysis across various domains, focusing on four main themes: feature extraction, classification, segmentation, and integration, demonstrating the transformative potential of these technologies.

The research of this programme is centered around dynamical systems, functional analysis, and their interplay.

Conference

Explore "Analysis of Repeated Measurements" at Boerhaave Nascholing. Learn statistical methods for correlated data in time. Read more here.

This handbook provides a resource for those already familiar with some kinds of micro-particles who wish to learn more about others, or for those just starting out in the study of microremains who wish to have a broad understanding about microscopic archaeology.

The Automated Design and Analysis of Algorithms (ADA) research group pursues the development of Artificial Intelligence techniques that complement, rather than replace, human intelligence.

The focus of the Multicriteria Optimization and Decision Analysis (MODA) group is to develop foundations of methods in multi-objective optimization.

The volume is one-stop shopping for crisis studies and a number of closely related fields, providing a window onto the latest thinking in the field. The articles reflect cutting edge, state of the art scholarship and pose key questions for research and practical development.

This thesis investigates the contribution of quantum computers to machine learning, a field called Quantum Machine Learning. Quantum Machine Learning promises innovative perspectives and methods for solving complex problems in machine learning, leveraging the unique capabilities of quantum computers…

The main methodological aspects of the use of stepwise LCA estimators under different circumstances.

Promotor: W.Th.F. den Hollander Co-Promotor: F.M. Spieksma

This thesis is based on five papers on several topics.

Analysis of neuroimaging data requires multiple steps where statistics play a crucial role. The MRI methods research group develops new statistical methods that are accurate, transparent and easy to use.

Systems pharmacology aims to apply techniques from systems biology to pharmacological models.

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This thesis seeks to combine two different research topics; Multi-Objective Optimization and Complex Network Analysis.

A research data infrastructure in computational social science

This MA explores contemporary literature and culture—art, film, pop music—through critical and theoretical lenses, including feminist theory, phenomenology, and ecocriticism. Key themes include diversity, interculturality, popular culture, and the intersection of culture, politics, and justice.

This thesis explores Breaking of Ensemble Equivalence (BEE) in random graph models by examining the spectral properties of adjacency matrices. The goal is to identify spectral characteristics that differentiate random graph ensembles, enhancing the understanding of complex network structures and beh…

Promotor: Prof.dr. E. Deprettere

Promotor: B. van de Water, Co-Promotores: J.H.N. Meerman, F.J. Verbeek

This study is a critical discourse analysis of the misogynistic narratives shared by three incel violent extremists.

Science is typically a patchwork of research contributions without much coordination. Especially in clinical trials, the follow-up studies that we do fail to be the most promising.

Optical projection tomography (OPT) is a tomographic 3D imaging technique used for specimens in the millimetre scale.

This dissertation advances automated negotiation by developing agents that can learn and adapt across diverse negotiation settings through three increasingly sophisticated approaches: automated algorithm configuration, portfolio-based strategy selection, and end-to-end reinforcement learning with graph…

In meta-analysis, heterogeneity often exists between studies. In such cases, it is essential to investigate the sources of heterogeneity and understand the relationship between effect size and study characteristics (i.e., moderators).