• Effective Volumetric Sculpting for Focus+Context Visualization, utilizing Implicitly Defined Surfaces and VR-on-Demand 

  Irgens, Marius (Master thesis, 2024-02-22)

• Implementing Structural Search and Replace for Showcasing ECMAScript Language Proposals 

  Glomsrud, Rolf Martin (Master thesis, 2024-06-07)

  Technical Committee 39 (TC39) of Ecma International is the body responsible for the evolution of the ECMAScript programming language, better known as JavaScript. Suggested changes to the language are presented in a form ...

• Tau Lepton Classification With Graph Neural Networks 

  Kristensen, Tobias Sagvaag (Master thesis, 2024-06-03)

  This thesis investigates the use of deep learning to classify tau leptons in high- energy physics experiments by employing Graph Neural Network (GNN)s. Tau leptons, unstable subatomic particles of the lepton class, decay ...

• Open APIs for Healthcare System Interoperability 

  Aarsæther, Anders Nilsen (Master thesis, 2024-06-03)

  The demographic changes in Norway are increasing the pressure on the Norwe- gian healthcare system to provide more efficient care. Adopting digital health technologies can address this challenge by making current healthcare ...

• Axiom Based Testing in Java 

  Nesse, Mads Bårvåg (Master thesis, 2024-06-03)

  Software plays a crucial role in today's society. Making sure that software is reliable is therefore very important. To make reliable software it is important to test it. Axiom-based testing gives us a way of specifying ...

• Flushable Promises: Modular Event Coalescing in Graphical User Interface Programming 

  Bonde, Maria Katrin (Master thesis, 2024-06-14)

  Graphical user interfaces (GUIs) are everywhere. They serve as the primary means of interaction between an application and its users. Developing GUIs with complex dataflows, where multiple elements depend on each other's ...

• From Data to Decisions: ML-Based Job Failure Analysis for the ALICE experiment 

  Skutlaberg, Erlend Lauvås (Master thesis, 2024-06-03)

  This paper researches the possibility of utilizing machine learning to locate factors contributing to a failing job at the ALICE grid, focusing on the grid site at the University of Bergen. A prototype system has been ...

• Least Surprising Dataflows in Constraint Based Graphical User Interfaces 

  Liland, Daniel Svalestad (Master thesis, 2024-06-10)

  There are many approaches for implementing Graphical User Interfaces (GUI) since programming GUIs is a difficult and complex task. This thesis focuses on a prticular GUI development approach, one based on multi-way dataflow ...

• Implementation and Evaluation of a Messaging Service for the Smart Ocean Platform 

  Jonasson, Jaran (Master thesis, 2024-06-03)

• Developing an Adaptive Planning Framework for Multi-Robot Missions 

  Heimvik, Dan Joar Isaksen (Master thesis, 2024-06-03)

• A Benchmarking Suite for Persistent Homology 

  Risanger, Sondre Bergsvåg (Master thesis, 2024-06-03)

• Exploring Methods for Quantifying Expressibility and Entangling Capability of Parameterized Quantum Circuits 

  Mjaaseth, Jørgen (Master thesis, 2024-06-03)

  Quantum Machine Learning (QML) is an exciting fusion of two disciplines, wherein classical machine learning techniques are augmented by quantum computation. Central to QML is the utilization of quantum bits, exploiting ...

• Stem cell identification via RNA sequencing in breast cancer. 

  Gimenez Devis, Cristobal (Master thesis, 2024-06-03)

  Breast cancer is a complex, heterogeneous disease with distinct cancer subtypes. When the breast organ develops, it has a large pool of mammary stem cells. These cells have the potential to give rise to the various cell ...

• Customized and Autonomous Learning in Computer Science: A conceptualized Learning Activity Recommendation System 

  Kavli, Sander Aasen (Master thesis, 2024-06-03)

• Diverting Networks with Odd Paths 

  Simonnes, Steinar (Master thesis, 2024-06-17)

  Problemet Kortest Odde Sti er å finne en sti fra en node til en annen i en graf, der antall kanter i stier må være et oddetall. Selv om problemet virker som kun intet annet enn en kuriøsitet, er verdien i det at mange ...

• Multitask variational autoencoders 

  Zakovskis, Edvards (Master thesis, 2024-06-03)

  Variational autoencoders (VAEs) are widely used for generative modeling and repre- sentation learning tasks. This thesis presents two novel approaches aimed at enhancing the performance of VAEs through the integration of ...

• Solving Maximum Weighted Matching problem using Graph Neural Networks 

  Zaicevs, Nikita (Master thesis, 2024-06-03)

  In this work we train a graph neural network model to solve the Maximum Weighted Matching problem on graphs using supervised learning. Unfortunately, the final results were below the set expectations. The model seemed to ...

• Simplest path betweenness centrality in embedded planar graphs 

  Oppegård, Vilde Dahl (Master thesis, 2024-06-03)

  In this thesis we present an alternative definition of distance, which aims to minimize the overall angle sum between adjacent edges in a path from s to t. In addition to this, we propose a corresponding centrality measure, ...

• Enhanced Anomaly Detection in Industrial Control Systems aided by Machine Learning 

  Berge, Vegard (Master thesis, 2024-05-29)

  This thesis investigates the potential of enhancing anomaly detection in Industrial Control Systems (ICS) through the integration of Machine Learning (ML) with traditional Network Intrusion Detection Systems (NIDS) and ...

• Bounding Algorithms for the Minimum Broadcast Time Problem 

  Sperrevik, Bendik (Master thesis, 2024-06-03)

  The minimum broadcast time problem concerns information dissemination in a graph given a set of initially informed nodes called source nodes. Each informed node can only inform at most one of its neighbors each time step. ...

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