Essays about: "neurala grafnätverk"

Found 4 essays containing the words neurala grafnätverk.

  1. 1. Traffic Prediction From Temporal Graphs Using Representation Learning

    University essay from KTH/Matematisk statistik

    Author : Andreas Movin; [2021]
    Keywords : Dynamic time warping DTW ; embedding; graph convolutional networks GCN ; graph neural networks GNN ; persistent homology; spectral graph theory; temporal graphs; topological data analysis TDA ; Dynamisk time warping DTW ; inbäddning; convolutional grafnätverk GCN ; neurala grafnätverk GNN ; persistent homologi; spektral graf teori; dynamisk graf; topologisk dataanalys TDA ;

    Abstract : With the arrival of 5G networks, telecommunication systems are becoming more intelligent, integrated, and broadly used. This thesis focuses on predicting the upcoming traffic to efficiently promote resource allocation, guarantee stability and reliability of the network. READ MORE

  3. 2. Money Laundering Detection using Tree Boosting and Graph Learning Algorithms

    University essay from KTH/Matematisk statistik

    Author : Rickard Frumerie; [2021]
    Keywords : Tree boosting; XGBoost; graph convolutional networks GCN ; node and edge neural networks NENN ; exploratory data analysis EDA ; anti money laundering AML ; financial graph networks.; Trädalgoritmer; XGBoost; convolutions grafnätverk GCN ; nod och kant neurala nätverk NENN ; utforskande dataanalys; penningtvättsbekämpning AML ; finansiella grafnätverk.;

    Abstract : In this masters thesis we focused on using machine learning methods for detecting money laundering in financial transaction networks, in order to demonstrate that it can be used as a complement or instead of the more commonly used rule based systems. The graph learning method graph convolutional networks (GCN) has been a hot topic in the field since they were shown to scale well with data size back in 2018. READ MORE

  4. 3. Gamma-ray tracking using graph neural networks

    University essay from KTH/Fysik

    Author : Mikael Andersson; [2021]
    Keywords : Physics; Nuclear Physics; Detectors; Tracking; Neural Networks; GNN; Gamma-ray; Fysik; Kärnfysik; Detektorer; Tracking; Neurala Nät; GNN; Gammastrålning;

    Abstract : While there are existing methods of gamma ray-track reconstruction in specialized detectors such as AGATA, including backtracking and clustering, it is naturally of interest to diversify the portfolio of available tools to provide us viable alternatives. In this study some possibilities found in the field of machine learning were investigated, more specifically within the field of graph neural networks. READ MORE

  5. 4. Using Graph Neural Networks for Track Classification and Time Determination of Primary Vertices in the ATLAS Experiment

    University essay from KTH/Matematisk statistik

    Author : Mattias Gullstrand; Stefan Maraš; [2020]
    Keywords : Time determination; graph neural network; graph attentional network; HGTD; vertex; node classification; particle physics; machine learning; Tidsbestämning; neurala grafnätverk; uppvaktande grafnätverk; HGTD; vertex; nodklassificering; partikelfysik; statistisk inlärning;

    Abstract : Starting in 2027, the high-luminosity Large Hadron Collider (HL-LHC) will begin operation and allow higher-precision measurements and searches for new physics processes between elementary particles. One central problem that arises in the ATLAS detector when reconstructing event information is to separate the rare and interesting hard scatter (HS) interactions from uninteresting pileup (PU) interactions in a spatially compact environment. READ MORE