Sökning: "Graf klustring"

Hittade 4 uppsatser innehållade orden Graf klustring.

1. 1. Properties of Discrete Laplacians With Application on Brain Networks

   Master-uppsats, KTH/Matematisk statistik

   Författare :David Thinsz; [2022]
   Nyckelord :Graph Laplacian; Combinatorial Laplacian; Persistent Laplacian; Topological data analysis; Spectral theory; Homology; Clustering.; Graf-Laplacian; Kombinatorisk Laplacian; Beständig Laplacian; Topologisk dataanalys; Spektralteori; Homologi; Klustring.;

   Sammanfattning : This thesis investigates three discrete Laplace operators: the graph Laplacian, combinatorial Laplacian, and the more recently introduced persistent Laplacian. We discuss how these operators relate to each other and study their spectral properties. The graph Laplacian is a well-studied operator that plays a central role in spectral graph theory. LÄS MER

3. 2. Synthetic Graph Generation at Scale : A novel framework for generating large graphs using clustering, generative models and node embeddings

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Johan Hammarstedt; [2022]
   Nyckelord :Data Anonymization; Graph Learning; Generative Graph Modeling; Graph Clustering; Node Embedding; Synthetic Data; Dataanonymisering; Grafinlärning; Generativa graf-modeller; Graf klustring; Länk prediktion; Nodinbäddning; Syntetisk data;

   Sammanfattning : The field of generative graph models has seen increased popularity during recent years as it allows us to model the underlying distribution of a network and thus recreate it. From allowing anonymization of sensitive information in social networks to data augmentation of rare diseases in the brain, the ability to generate synthetic data has multiple applications in various domains. LÄS MER

4. 3. Klustring av bilder med Wassersteinavstånd och Sinkhorn-Knopp iteration

   Kandidat-uppsats, KTH/Skolan för teknikvetenskap (SCI)

   Författare :Alex Norlin; [2021]
   Nyckelord :;

   Sammanfattning : I denna studie implementeras och testas en metod för att masskatagorisera bilder som bygger på Wassersteinavståndet mellan bilderna. Wassersteinavståndet beräknas med hjälp av Sinkhorn-Knopp iteration. Avståndet används för att beräkna en viktad graf som sedan klustras med en spektralklustringsalgoritm. LÄS MER

5. 4. Road traffic congestion detection and tracking with Spark Streaming analytics

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Thorsteinn Thorri Sigurdsson; [2018]
   Nyckelord :streaming; graph processing; congestion; community detection; connected components;

   Sammanfattning : Road traffic congestion causes several problems. For instance, slow moving traffic in congested regions poses a safety hazard to vehicles approaching the congested region and increased commuting times lead to higher transportation costs and increased pollution. LÄS MER