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Solà Roca, Albert (author)
Water distribution networks (WDNs) provide drinking water to urban and rural consumers through a network of pipes that transport water from reservoirs to junctions. Water utilities rely on tools such as EPANET to simulate and analyse the performance of water distribution networks (WDNs). EPANET solves the flow continuity and headloss equations...
master thesis 2023
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Möllers, Alex (author)
In this thesis we develop a Bayesian approach to graph contrastive learning and propose a new uncertainty measure based on the disagreement in likelihood due to different positive samples. Moreover, we extend contrastive learning to simplicial complexes and show that it can be used to generate high-quality representations of edge flow data.
master thesis 2023
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Naber, Titus (author)
master thesis 2023
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Lodha, Sneha (author)
<br/>One of the contributing factors to climate change is the release of gases, particularly carbon dioxide (CO2), which is amplified by the expanding E-commerce industry. E-commerce enterprises heavily depend on recommender systems as a means to incentivize consumers towards making product purchases. This master's thesis investigates the...
master thesis 2023
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Liu, Chengen (author)
The edge flow reconstruction task improves the integrity and accuracy of edge flow data by recovering corrupted or incomplete signals. This can be solved by a regularized optimization problem, and the corresponding regularizers are chosen based on prior knowledge. However, obtaining prior information is challenging in some fields. Thus, we...
master thesis 2023
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Dahrs, Simon (author)
Recommender systems help users to find items they presumably like based on data collected on that user. Collaborative filtering is arguably the most common recommendation system technique. It uses collected ratings to compute similarities between users and recommends items based on those similarities. With that, a problem arises when there are...
master thesis 2022
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Kalisvaart, Raoul (author)
We all know the possible consequences of global warming, rising temperatures, flooded cities and destroyed ecosystems. One of the causes is the emission of gases, predominantly CO2, which is increased by the growing E-commerce market. E-commerce companies rely on recommender systems to stimulate users to purchase products. We are convinced that...
master thesis 2022
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Monté, Sérénic (author)
Collaborative filtering is used to predict the preference or rating of a user for a certain item. Collaborative filtering is based on the notion that similar users rate similarly. A lot of research is done on how to improve this algorithm, mostly with deep learning. A less investigated field for recommender systems is graph signal processing....
bachelor 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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van Blokland, Lars (author)
Algorithms that recommend items to users are known as recommender systems and have become an important part of online ecosystems. These systems calculate the similarity between given users or items based on the ratings they have received. Such similarities can be modeled as a graph where users or items (nodes) have connections (edges) to other...
bachelor thesis 2022
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Krisiukėnas, Pijus (author)
Due to the devastating consequences of earthquakes, predicting their occurrence before the first strike has been a long standing research topic. Deep learning models have been used to facilitate prediction, using seismograph data to attempt to classify an earthquake right before it happens. However, this is a difficult task and research needs to...
bachelor thesis 2022
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Zhu, Kevin (author)
Earthquake prediction is the field of seismology concerned with predicting the time, location, and magnitude of earthquakes within a small time frame, usually defined in terms of minutes or seconds before an event. Such predictions can have a large impact on minimizing the damage caused by these seismic events, by providing early warnings to the...
bachelor thesis 2022
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Koper ook geschreven Jansen, Melle (author)
A recommendation algorithm aims to predict the quality of a user's future interaction with certain items based on their previous interactions. As research progresses, these algorithms are becoming increasingly more complicated with the use of machine learning and neural networks. This paper looks into a more simple solution. The recommendation...
bachelor thesis 2022
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Georgiev, Gancho (author)
Earthquakes are one of the most destructive natural phenomena, both in terms of human lives, and property damage. Although they are treated as a random phenomenon, the ability to predict them, even few seconds before they occur, could be of great benefit to society. Lots of research has been done on this topic but without any significant results...
bachelor thesis 2022
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Houbaer, Maikel (author)
Earthquakes can do great harm to the environment and people's daily lives. Being able to predict an earthquake moments before it happens could therefore reduce harm and save human lives. Traditional methods have not been successful yet, but with the rise of techniques focused on deep learning, there is a growing interest to apply them to the...
bachelor thesis 2022
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van den Akker, Daniel (author)
Multi-Layer Perceptron and Support Vector Machine have both been widely used in machine learning. In this research paper, these models have been applied to binary classification on an individual time series basis. The goal was to see whether they can predict earthquakes, using earthquakes measured at specific stations across New Zealand. As it...
bachelor thesis 2022
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Du, XIANGYU (author)
Earthquake prediction has raised many concerns nowadays, due to the massive loss caused by earthquakes, as well as the significance of accurate forecasting. Lots of trials have been investigated and experimented but few achieved satisfying results on short-term prediction (i.e., usually those earthquakes that will happen in three months). It is...
bachelor thesis 2022
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Hashmi, Irtaza (author)
Earthquakes are one of the most dangerous natural disasters that occur worldwide. Predicting them is one of the unsolved problems in the field of science. In the past decade, there has been an increase in seismic monitoring stations worldwide, which has allowed us to design and implement data-driven and deep learning solutions. In this paper, we...
bachelor thesis 2022
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Zin, Gaia (author)
Epilepsy is one of the most common neurological disorders worldwide. Its manifestations, the seizures, are due to a group of neurons' abnormal and synchronous activity. The unpredictable nature of these events hinders the quality of life of those affected. In particular, focal seizures show a localized onset of the abnormal activity and are the...
master thesis 2021
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de Bruijn, Vasco (author)
In cyber security, side-channel attacks (SCA) are of interest because they target the vulnerabilities in implementation rather than inherent vulnerabilities in the algorithm. Profiled SCA is especially interesting as it assumes that the adversary has unlimited access to a clone device that can generate sufficient traces to create a profile of...
master thesis 2021
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