Essays about: "Topologisk Data Analys"

Showing result 1 - 5 of 11 essays containing the words Topologisk Data Analys.

  1. 1. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis

    University essay from KTH/Matematik (Avd.)

    Author : Nazar Maksymchuk Netterström; [2023]
    Keywords : Recurrent Neural Network; Long-Short-Term-Memory; Topological Data Analysis; Session based data; Anomaly detection; Time-series analysis; Imbalanced data; Master thesis; Neurala nätverk; Topologisk data analys; Detektion av avvikelse; Sessionsbaserad data; Tidserieanalys; Inbalancerad data; Masteruppsats;

    Abstract : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. READ MORE

  2. 2. Exploring persistent homology as a method for capturing functional connectivity differences in Parkinson’s Disease.

    University essay from KTH/Matematik (Avd.)

    Author : Naomi Hulst; [2022]
    Keywords : persistent homology; topological data analysis; computational topology; parkinson s disease; parkinson; functional connectivity; stable rank; ihållande homologi; topologisk data analys; beräknings topologi; Parkinsons sjukdom; parkinson; funktionell konnektivitet; stable ranks;

    Abstract : Parkinson’s Disease (PD) is the fastest growing neurodegenerative disease, currently affecting two to three percent of the population over 65. Studying functional connectivity (FC) in PD patients may provide new insights into how the disease alters brain organization in different subjects. READ MORE

  3. 3. Towards topology-aware Variational Auto-Encoders : from InvMap-VAE to Witness Simplicial VAE

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Aniss Aiman Medbouhi; [2022]
    Keywords : Variational Auto-Encoder; Nonlinear dimensionality reduction; Generative model; Inverse projection; Computational topology; Algorithmic topology; Topological Data Analysis; Data visualisation; Unsupervised representation learning; Topological machine learning; Betti number; Simplicial complex; Witness complex; Simplicial map; Simplicial regularization.; Variations autokodare; Ickelinjär dimensionalitetsreducering; Generativ modell; Invers projektion; Beräkningstopologi; Algoritmisk topologi; Topologisk Data Analys; Datavisualisering; Oövervakat representationsinlärning; Topologisk maskininlärning; Betti-nummer; Simplicielt komplex; Vittneskomplex; Simpliciel avbildning; Simpliciel regularisering.;

    Abstract : Variational Auto-Encoders (VAEs) are one of the most famous deep generative models. After showing that standard VAEs may not preserve the topology, that is the shape of the data, between the input and the latent space, we tried to modify them so that the topology is preserved. READ MORE

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

    University essay from KTH/Matematisk statistik

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

    Abstract : 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. READ MORE

  5. 5. From Relations to Simplicial Complexes: A Toolkit for the Topological Analysis of Networks

    University essay from KTH/Matematik (Avd.)

    Author : Johan Lord; [2021]
    Keywords : applied algebraic topology; complex networks; topological data analysis; brain network analysis;

    Abstract : We present a rigorous yet accessible introduction to structures on finite sets foundational for a formal study of complex networks. This includes a thorough treatment of binary relations, distance spaces, their properties and similarities. READ MORE