Department of Informatics: Recent submissions

Now showing items 121-140 of 1130

    • Loss-function learning for cell type mapping of spatial transcriptomics using single-cell RNA-seq data 

      Skaar, Ørjan Løseth (Master thesis, 2023-06-01)
      Breast cancers are complex cellular ecosystems consisting of multiple cell types. Heterotypic interactions and their unique gene expression profiles play central roles in cancer progression and response to therapy. However, ...

    • A Functional Implementation of a Multiway Dataflow Constraint System Library 

      Aanes, Bo Victor Isak (Master thesis, 2023-06-16)

    • Object Tracking Approach for Catch Estimation on Trawl Surveys 

      Liessem, Peter Løkhammer (Master thesis, 2023-06-16)
      In the Norwegian Sea, coordinated multinational surveys are regularly undertaken with the aim of assessing the size and composition of marine life populations - a fundamental practice for ensuring long-term ecological ...

    • An Algorithm for k-insertion into a Binary Heap 

      Berg, Marie Natland (Master thesis, 2023-06-01)
      In this thesis, we present an algorithm for k-insertion into a binary heap running in worst-case time O(k+log(k)·log(n+k)), improving the standard k-insertion algorithm for binary heaps in terms of worst-case running time. ...

    • Deep Learning Approach To Gene Network Inference 

      Johannessen, Daniel Hammerstad (Master thesis, 2023-06-01)
      Gene regulatory network(GRN) inference remains a challenging problem in the field of bioinformatics. GRN contain valuable information needed to get a deeper understanding of the regulatory network. This could lead to ...

    • Generic programming using Higher Kinded Data 

      Frid, Kathryn (Master thesis, 2023-06-28)
      This thesis describes datatype-generic programming, what it is, and how it is done in Scala. The thesis covers ways of thinking about datatype-generic programming and today's tools and libraries for datatype-generic ...

    • Multi-List Recommendations for Personalizing Streaming Content 

      Vlasenko, Anastasia (Master thesis, 2023-06-01)
      The decision behind choosing a recommender system that yields accurate recommendations yet allows users to explore more content has been a topic of research in the last decades. This work attempts to find a recommender ...

    • Parallel Community Detection in Incremental Graphs 

      Tønnessen, Magnus (Master thesis, 2023-06-02)
      The problem of community detection in large, expanding real-world networks presents significant challenges due to the scale and complexity of these networks. Traditional algorithms struggle to provide optimal solutions or ...

    • Lattice Sieving With G6K 

      Moksheim, Katrine (Master thesis, 2023-06-01)
      Recent advances in quantum computing threaten the cryptography we use today. This has led to a need for new cryptographic algorithms that are safe against quantum computers. The American standardization organization NIST ...

    • Combining Query Rewriting and Knowledge Graph Embeddings for Complex Query Answering 

      Imenes, Anders (Master thesis, 2023-06-01)
      The field of complex query answering using Knowledge Graphs (KGs) has seen substantial advancements in recent years, primarily through the utilization of Knowledge Graph Embeddings (KGEs). However, these methodologies often ...

    • Enhanced biomedical data extraction from scientific publications 

      Berggrav, Markus Almendral (Master thesis, 2023-06-01)
      The field of scientific research is constantly expanding, with thousands of new articles being published every day. As online databases grow, so does the need for technologies capable of navigating and extracting key ...

    • Consistency of LSO with syntactic equality 

      Spörl, Yannick (Master thesis, 2023-06-01)
      LSO, Logic of Sentential Operators, is defined by extending first- order logic by sentential quantification and sentential operators. Its semantics is defined by a digraph, with kernels reflecting consistent valuations of ...

    • Rule learning of the Atomic dataset using Transformers 

      Æsøy, Kristoffer (Master thesis, 2023-06-02)
      Models used for machine learning are used for a multitude of tasks that require some type of reasoning. Language models have been very capable of capturing patterns and regularities found in natural language, but their ...

    • Introduction to Lattices and Its Applications in Compute-and-Forward Strategy 

      Lidsheim, Maria van der Reek (Master thesis, 2023-06-01)
      The Compute-and-Forward (CF) strategy was proposed as a physical layer network coding (PNC) framework by Nazer and Gastpar in 2011. CF exploits interference to obtain higher rates between users in a network. This thesis ...

    • Tail-biting Codes for Lattice Wiretap Coding 

      Persson, Palma Rud (Master thesis, 2023-06-01)
      The secrecy gain of Construction A lattices obtained by tail-biting rate 1/2 convolutional codes is studied to evaluate the secrecy performance of a lattice in a wiretap channel communication. The higher the secrecy gain, ...

    • On Derivative-Free Optimisation Methods 

      Heeman, Pim (Master thesis, 2023-05-15)
      As part of the field of mathematical optimisation, derivative-free optimisation is the study of optimisation methods that are not granted full access to the derivative of the objective function. In this master's thesis, ...

    • Reinforcement Learning for Lifelong Multi-Agent Pathfinding in AutoStore system 

      Djupesland, Elias Eriksen (Master thesis, 2023-05-25)
      AutoStore (AS) uses a cubic system for warehouse automation, utilizing robots to retrieve and organize objects in a three-dimensional grid of bins in a Manhattan geometry environment. Lifelong Multi-Agent Pathfinding (LMAPF) ...

    • On a New, Efficient Framework for Falsifiable Non-interactive Zero-Knowledge Arguments 

      Parisella, Roberto (Doctoral thesis, 2023-06-09)
      Et kunnskapsløst bevis er en protokoll mellom en bevisfører og en attestant. Bevisføreren har som mål å overbevise attestanten om at visse utsagn er korrekte, som besittelse av kortnummeret til et gyldig kredittkort, uten ...

    • A general deep reinforcement learning hyperheuristic framework for solving combinatorial optimization problems 

      Kallestad, Jakob Vigerust; Hasibi, Ramin; Hemmati, Ahmad; Sörensen, Kenneth (Journal article; Peer reviewed, 2023)
      Many problem-specific heuristic frameworks have been developed to solve combinatorial optimization problems, but these frameworks do not generalize well to other problem domains. Metaheuristic frameworks aim to be more ...

    • A survey of parameterized algorithms and the complexity of edge modification 

      Crespelle, Christophe; Drange, Pål Grønås; Fomin, Fedor; Golovach, Petr (Journal article; Peer reviewed, 2023)
      The survey is a comprehensive overview of the developing area of parameterized algorithms for graph modification problems. It describes state of the art in kernelization, subexponential algorithms, and parameterized ...