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.

Onderzoeken hoe gegevens afkomstig van draagbare technologieën kunnen worden gebruikt om effectieve gedragsveranderingen te identificeren die hopelijk zullen leiden tot gezondheidsverbeteringen.

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…

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.

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

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…

Discover "Meta Analysis" at Boerhaave Nascholing. Explore risk analysis, models, and advanced topics. Elevate your understanding. Read more here.

Explore "Regression Analysis" at Boerhaave Nascholing. Gain expertise in biostatistics methods for accurate data interpretation. Read more here.

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.

In 2018, the number of mobile phone users will reach about 4.9 billion. Assuming an average of 5 photos taken per day using the built-in cameras would result in about 9 trillion photos annually.

Discover "Meta Analysis" at Boerhaave Nascholing. Explore risk analysis, models, and advanced topics. Elevate your understanding. Read more here.

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

Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…

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

Learning from small data sets in machine learning is a crucial challenge, especially when dealing with data imbalances and anomaly detection. This thesis delves into the challenges and methodologies of learning from small datasets in machine learning, with a particular focus on addressing data imbalances…

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

Het onderzoek van dit programma is gecentreerd rond dynamische systemen, functionele analyse en hun interactie.

Explore "Regression Analysis" at Boerhaave Nascholing. Gain expertise in biostatistics methods for accurate data interpretation. Read more here.

Promotor: J. N. Kok, Co-promotor: A. J. Knobbe

In this dissertation (titled: Exploring the Synergies between Transfer in Reinforcement Learning and Procedural Content Generation) we explore how the two research fields named in the title, namely Transfer in Reinforcement Learning (TRL) and Procedural Content Generation (PCG) can synergize togethe…

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.

With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically.

The invention of neural networks marks a critical milestone in the pursuit of true artificial intelligence. Despite their impressive performance on various tasks, these networks face limitations in learning efficiently as they are often trained from scratch.

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.

This thesis is based on five papers on several topics.

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

This thesis advances automata learning, a key area in computer science, with applications in software verification, biological analysis, and autonomous technologies. It explores three main themes: first, it introduces a passive learning algorithm for generating compact probabilistic models from positive…

De masteropleiding Cultural Analysis: Literature and Theory van de Universiteit Leiden richt zich op de studie van literatuur vanuit een vergelijkend en theoretisch perspectief, en onderzoekt de literatuur van een breed spectrum van talen en culturen uit de hele wereld.

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

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…

Transport inspectorates are looking for novel methods to identify dangerous behavior, ultimately to reduce risks associated to the movements of people and goods. We explore a data-driven approach to arrive at smart inspections of vehicles.

Explaining treatment response variability between and within patients can support treatment and dosing optimization, to improve treatment of individual patients.

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

This thesis mainly focuses on multimodal understanding and Visual Question Answering (VQA) via deep learning methods. For technical contributions, this thesis first focuses on improving multimodal fusion schemes via multi-stage vision-language interactions.

Promotor: Prof.dr. E. Deprettere

Promotor: Prof.dr. B. van de Water

This thesis mainly focuses on cross-modal retrieval and single-modal image retrieval via deep learning methods, i.e. by using deep convolutional neural networks.

Computers zijn in staat om ongelooflijk nauwkeurige voorspellingen te doen op basis van machine learning. Met andere woorden, deze computers kunnen zonder tussenkomst leren als ze eenmaal door mensen zijn voorgeprogrammeerd. Bij LIACS verkennen en verleggen we de grenzen van wat een revolutionaire nieuwe…

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.

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…

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).

Promotores: T.H.W. Bäck, A. Plaat, Co-promotor: F.J. Verbeek

We are living in an information era where the amount of image and video data increases exponentially.

The chemical and structural heterogeneity of toxoid vaccines makes their analysis challenging. However, detailed insights on a molecular level can be obtained by mass spectrometry.

Automated Machine Learning (AutoML) is widely used to automatically build a suitable practical Machine Learning (ML) model for an arbitrary real-world problem, reducing the effort of practitioners in the ML development cycle for real-world applications. Optimization is a key part of a typical AutoML…

Op welke manier kunnen docenten de betrokkenheid van studenten ondersteunen en vergroten in de context van blended learning?

We have studied shape with a particular focus on the zebrafish model system. The shape is an essential appearance of the phenotype of a biological specimen and it can be used to read out a current state or response or to study gene expression.

Learning about My meaningful Way through life and profession.

Sewer pipes are an essential infrastructure in modern society and their proper operation is important for public health. To keep sewer pipes operational as much as possible, periodical inspections for defects are performed.