Sökning: "stokastisk process"

Visar resultat 1 - 5 av 28 uppsatser innehållade orden stokastisk process.

  1. 1. A Study of the Loss Landscape and Metastability in Graph Convolutional Neural Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Sofia Larsson; [2020]
    Nyckelord :Graph neural networks; Graph convolutional neural networks; Loss landscape; Gradient descent; Stochastic gradient descent; Stochastic gradient Langevin dynamics; Grafneurala nätverk; grafiska faltningsnätverk; lösningslandskap; gradientmetoder; stokastiska gradientmetoder; stokastisk gradient Langevin dynamik;

    Sammanfattning : Many novel graph neural network models have reported an impressive performance on benchmark dataset, but the theory behind these networks is still being developed. In this thesis, we study the trajectory of Gradient descent (GD) and Stochastic gradient descent (SGD) in the loss landscape of Graph neural networks by replicating Xing et al. LÄS MER

  2. 2. Stochastic Modelling of Cash Flows in Private Equity

    Master-uppsats, KTH/Matematisk statistik

    Författare :Oscar Ungsgård; [2020]
    Nyckelord :Private Equity; Stochastic Process; Cash flow forecasting; value at risk; monte carlo; Private Equity; Stokastisk Process; Cash flow forecasting; value at risk; monte carlo;

    Sammanfattning : An investment in a private equity is any investment made in a financial asset that is not publicly traded. As such these assets are very difficult to value and also give rise to great difficulty when it comes to quantifying risk. LÄS MER

  3. 3. Sequence Prediction for Identifying User Equipment Patterns in Mobile Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Theoharis Charitidis; [2020]
    Nyckelord :Markov chain; mobile networks; user equipment; machine learning; statistics; sequence prediction; stochastic process; Maskininlärning; mobila nätverk; statistik; markovkedjor; all k order markov; stokastisk process; sekvensprediktering;

    Sammanfattning : With an increasing demand for bandwidth and lower latency in mobile communication networks it becomes gradually more important to improve current mobile network management solutions using available network data. To improve the network management it can for instance be of interest to infer future available bandwidth to the end user of the network. LÄS MER

  4. 4. Point Process Based Phoneme Recognition Acceleration

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

    Författare :Hongliang Qiu; [2019]
    Nyckelord :;

    Sammanfattning : Stochastic gradient descent (SGD) is the core technology to train a deep learning model. It is well known that SGD suffers from the variance of gradients in each iteration. Deep learning has already been widely used in many applications because of its great performance in tasks such as image recognition. LÄS MER

  5. 5. Hydropower Modelling of Continental Europe Using EMPS

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

    Författare :Rebeca Brenes Brenes; [2019]
    Nyckelord :;

    Sammanfattning : Flexible hydropower plays a vital role when integrating large shares of variablerenewable generation in the power system. This project proposes a method forcreating a stochastic model for hydropower in Continental Europe using EMPS, apower market simulator software that specialises on hydrothermal power systems. LÄS MER