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Kirbeyi, Doruk (author)This research explores the landscape of dataset generation through the lens of Probabilistic Principal Component Analysis (PPCA) and β-Conditional Variational Auto-encoder (β-CVAE) models. We conduct a comparative analysis of their respective capabilities in reproducing datasets that mirror the distribution of the original data that comes from a...bachelor thesis 2024
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Taklimi, Sam (author)The objective of this project is to train a model that transforms a tree with its foliage into only its branch structure. This is achieved by employing machine-learning techniques, specifically Generative Adverserial Networks (GANs). By utilizing the proposed method, a predictive model is built that automatically minimizes its own error function...bachelor thesis 2024
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de Goede, Matthijs (author)The training of diffusion-based models for image generation is predominantly controlled by a select few Big Tech companies, raising concerns about privacy, copyright, and data authority due to the lack of transparency regarding training data. Hence, we propose a federated diffusion model scheme that enables the independent and collaborative...bachelor thesis 2023
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Vărzaru, REBECA (author)Code generation is becoming one of the most important tools in an Integrated Development Environment (IDE) for programmers, be they novices or experts. It allows them to produce code faster, avoid typos and other mistakes, be more efficient and easily turn ideas into code. As such, there are many in-IDE code generation models to choose from,...bachelor thesis 2023
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Sochirca, Dan (author)Code generation models have become more popular recently, due to the fact that they assist developers in writing code in a more productive manner. While these large models deliver impressive performance, they require significant computational resources and memory, making them difficult to deploy and expensive to train. Additionally, their large...bachelor thesis 2023
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Neagu, Alexandra (author)In recent years, significant progress has been made in the field of natural language processing (NLP) through the development of large language models (LLMs) like BERT and ChatGPT. These models have showcased remarkable abilities across a range of NLP tasks. However, effectively harnessing their potential requires meticulous prompt engineering...bachelor thesis 2023
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Cambaz, Doga (author)The recent emergence of AI-driven code generation models can potentially transform programming education. To pinpoint the current state of research on using AI code generators to support learning and teaching programming, we conducted a systematic literature review with 21 papers published since 2018. The review presents the teaching and...bachelor thesis 2023
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GEORGIADES, IOANNIS (author)With the following paper we are planning to present and explore the possibilities of the the newly introduced Poisson Flow Generative Model (PFGM). More specifically, this work aims to introduce the Conditional Poisson Flow Generative Model (CoPFGM), which by extending the existing repository of the PFGM, it will be able to be trained in a way...bachelor thesis 2023
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Mercier, Arthur (author)Reconstructing seen images from functional magnetic resonance imaging (fMRI) brain scans has been a growing topic of interest in the field of neuroscience, fostered by innovation in machine learning and AI. This paper investigates the possible presence of personal features allowing the identification of subjects from their reconstructed images....bachelor thesis 2023
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Schriemer, Sterre (author)Frequentist statistics and Bayesian statistics are the two main approaches to statistical inference. The frequentist approach is commonly integrated into academic curricula, while the Bayesian approach is less frequently employed. However a comparison of the approaches, further investigating their shortcomings and advantages, might give a better...bachelor thesis 2023
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Dicke, Linge (author)Background:<br/>Cancer is one of the leading causes of death worldwide. Targeted radionuclide therapy has become a important treatment, this is when a carrier molecule is attached to a radionuclide to deliver cytotoxic radiation levels to diseased cells. β<br/>− emitters are frequently used in RNT because they have a long penetration depth, such...bachelor thesis 2023
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Chang, Jakka (author)The Generalized Gamma Distribution (GGD) is a three-parameter distribution with desirable properties. For certain values of the parameters, the GGD can reduce to the gamma, exponential and lognormal distribution, among others. This makes it a flexible distribution that can be used in various scenarios. The problem with implementation of the GGD...bachelor thesis 2022
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Hoogeveen, Harm (author)Commonsense knowledge plays a key role in human intelligence. It is knowledge possessed by most humans that helps them in everyday situations. One possible way is to store the knowledge in four types. Each piece is either positive or negative, and generative or discriminative. For efficient retrieval and storage, a uniform model is needed....bachelor thesis 2022
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van Lith, Jochem (author)Learning algorithms can perform poorly in unseen environments when they learn<br/>spurious correlations. This is known as the out-of-domain (OOD) generalization problem. Invariant Risk Minimization (IRM) is a method that attempts to solve this problem by learning invariant relationships. Motivating examples as well as counterexamples have been...bachelor thesis 2022
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Guan, Zenan (author)Out-of-Domain (OOD) generalization is a challenging problem in machine learning about learning a model from one or more domains and making the model perform well on an unseen domain. Empirical Risk Minimization (ERM), the standard machine learning method, suffers from learning spurious correlation in the training domain, therefore may perform...bachelor thesis 2022
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Liu, Anxian (author)Out-of-domain (OOD) generalization refers to learning a model from one or more different but related domain(s) that can be used in an unknown test domain. It is challenging for existing machine learning models. Several methods have been proposed to solve this problem, and multi-domain calibration is one of these methods. Model selection with the...bachelor thesis 2022
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van Oudenhoven, Vincent (author)An empirical study is performed exploring the sensitivity to hidden confounders of GANITE, a method for Individualized Treatment Effect (ITE) estimation. Most real world datasets do not measure all confounders and thus it is important to know how crucial this is in order to obtain comparable predictions. This is explored through the removal of...bachelor thesis 2022
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Çelebi, Betul Irmak (author)Generative Adversarial Networks (GANs) brought rapid developments in generating synthetic images by mimicking structures in the training data. With the list of application of GANs growing drastically, it has lately become an exciting technology to explore for designers to communicate their ideas and arts through technology and create engaging...bachelor thesis 2022
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Jehee, Wouter (author)Federated learning (FL), although a major privacy improvement over centralized learning, is still vulnerable to privacy leaks. The research presented in this paper provides an analysis of the threats to FL Generative Adversarial Networks. Furthermore, an implementation is provided to better protect the data of the participants with Trusted...bachelor thesis 2022
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Gommers, Pieter (author), Ottink, Loran (author)In this thesis the build plans for a new residential neighbourhood are used as a basis for a distribution network of the neighbourhood of the future. Data is used to simulate power flows and an analysis is given on the current method used by DSO's. Furthermore the discussion is opened to suggest different methods for constructing sustainable...bachelor thesis 2022