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van den Bogaard, Fenna (author)
The origin of the Martian dichotomy is subject to question and no substantial evidence exists. Some surface and interior features that are not visible in, e.g., topography data, can show up in gravity data. Therefore, this research inverts gravity data to find a crustal and mantle global density model. Previous research performed a one-layer...
master thesis 2024
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Alwani, Neil (author)
This study investigates the application of generative models for synthetic data generation in pathway optimization experiments within the field of metabolic engineering. Conditional Variational Autoencoders (CVAEs) use neural networks and latent variable distributions to generate new, plausible data samples. We adapt this model by conditioning...
bachelor thesis 2024
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Stol, Madelon (author)
Understanding the role of genes and genetic variants is a key challenge in unraveling the driving mechanisms of Alzheimer's disease (AD). Single-cell RNA sequencing is a technique that quantifies gene expression at the cell (type) level enabling investigation of the roles of different cell types in disease. We analyzed changes in gene (co-...
master thesis 2023
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Schipper, Wieger (author)
In this thesis, we study a particle method for Bayesian deep learning. In particular, we look at the estimation of the parameters of an ensemble of Bayesian neural networks by means of this particle method, called Stein variational gradient descent (SVGD). This method iteratively updates a collection of parameters and it has the property that...
master thesis 2023
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Bettini, Andrea (author)
This thesis presents an energy-conservative data-driven approach in modelling the closure terms of the Navier-Stokes equations casted through the Variational Multiscale (VMS) framework. For context, the VMS framework is applied in designing stabilised finite element methods for multiscale phenomena in which stability is not guaranteed. Under...
master thesis 2023
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van Amerongen, Maximilian (author)
Artificial Neural Networks (ANNs) have emerged as a powerful tool for classification tasks due to their ability to outperform traditional methods. Nevertheless, their effectiveness relies heavily on the availability of large, varied, and labeled datasets, which are often not available. To counter this constraint, data augmentation techniques...
master thesis 2023
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LIU, Xinjie (author)
Many autonomous navigation tasks require mobile robots to operate in dynamic environments involving interactions between agents. Developing interaction-aware motion planning algorithms that enable safe and intelligent interactions remains challenging. Dynamic game theory renders a powerful mathematical framework to model these interactions...
master thesis 2023
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Sterrenberg, Amy (author)
Energy use, CO2 emissions, and waste production are all significant causes of environmental issues. The building sector is a major contributor to these problems, specifically the manufacturing of (structural) steel elements. Application of reuse and/or remanufacturing, as done in a circular economy, will reduce these effects. Therefore, these...
master thesis 2023
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Madhavan, Aravind Krishna (author)
This investigation focuses on the premixed conical flame, a mainstay of combustion diagnostics. While extensive studies have explored high-frequency oscillations in the canonical Bunsen flame, little attention has been given to low-frequency oscillations affecting flame fronts. This thesis aims to explain the origins of these oscillations and...
master thesis 2023
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Lenferink, Luc (author)
The ability to model other agents can be of great value in multi-agent sequential decision making problems and has become more accessible due to the introduction of deep learning into reinforcement learning. In this study, the aim is to investigate the usefulness of modelling other agents using variational autoencoder based models in partially...
master thesis 2023
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Wegener, Malte (author)
Reconstructed Discontinuous Galerkin (rDG) methods aim to provide a unified framework between Discontinuous Galerkin (DG) and finite volume (FV) methods. This unification leads to a new family of spatial discretization schemes from order three upwards. The first of these new schemes is the rDG(P1P2) method, which represents the solution on each...
master thesis 2022
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Verduyn, Thomas (author)
The need of computational power for engineering applications has been ever increasing and with classical computers approaching their physical limits, new ways of improvement have to be investigated. One of the promising solutions is quantum computing. Most engineering problems require solving a system of linear equations of higher dimensions and...
master thesis 2022
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Shrestha, Suyash (author)
Structure-preserving or mimetic discretisations are a class of advanced discretisation techniques derived by employing concepts from differential geometry. Such techniques can attain specific conservation properties at the discrete level such as conservation of mass, kinetic energy, etc when applied to conservation laws. However, like...
master thesis 2022
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Saha, Paulam (author)
As global air traffic has continued to grow overthe past two decades, it has...
master thesis 2022
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Singh, Anuj (author)
The versatility to learn from a handful of samples is the hallmark of human intelligence. Few-shot learning is an endeavour to transcend this capability down to machines. Inspired by the promise and power of probabilistic deep learning, we propose a novel variational inference network for few-shot classification (coined as TRIDENT) to decouple...
master thesis 2022
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Drummer, Francesca (author)
Single-cell sequencing allows measuring individual cells' molecular features and their responses to perturbations. Understanding which cells respond to a particular perturbation and how these responses vary across populations can be used to, for example, improve vaccine immunogenicity. However, an exhaustive exploration of single-cell...
master thesis 2022
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Mariūnas, Karolis (author)
Recommender systems (RS) assist users in making decisions by filtering content that the user would likely find relevant. Standard techniques like collaborative filtering exploit user similarities to find the recommendations assuming that similar users are likely to be interested in the same items. On the other hand, graph RS borrow techniques...
bachelor thesis 2022
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Julian Villena, Leyre (author)
This master thesis report is the result of a six-month-long graduation project for the Design for Interaction master at TU Delft. The report describes the development of the design guidelines to attune the TAS program to the Netherlands.<br/>The main goals that guided the project were three: identify which aspects of a healthy habit program (TAS...
master thesis 2022
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REN, Zhenlu (author)
The continuous accumulation of solid waste has posed a great threat to the environment of our future generations. A novel approach that is currently under development is to treat the waste collected in an engineered landfill in order to reduce the emission potential to an environmentally acceptable level. The main topic for this research is to...
master thesis 2021
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Niezen, Robin (author)
Miniaturizing mechanical tessellations with rigid origami behavior is difficult since rigid origami can only be approached in real mechanical systems. Rigid-origami means that the fold-lines have zero stiffness, and the facets have infinite stiffnes. However, zero stiffness and infinite stiffness can physically not be obtained. To approach the...
master thesis 2021
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