Sökning: "Statistisk inlärning"

Visar resultat 11 - 15 av 28 uppsatser innehållade orden Statistisk inlärning.

1. 11. Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces

   Master-uppsats, KTH/Matematisk statistik

   Författare :Christopher Herron; André Zachrisson; [2020]
   Nyckelord :Applied Mathematics; Machine Learning; Statistics; Gaussian Process; Neural Network; Options; Volatility; Implied Volatility Surface; Black Scholes; Tillämpad matematik; Maskininlärning; Statistik; Gaussisk Process; Neurala Nätverk; Optioner; Volatilitet; Implicit Volatilitetsyta; Black Scholes;

   Sammanfattning : The implied volatility surface plays an important role for Front office and Risk Management functions at Nasdaq and other financial institutions which require mark-to-market of derivative books intraday in order to properly value their instruments and measure risk in trading activities. Based on the aforementioned business needs, being able to calibrate an end of day implied volatility surface based on new market information is a sought after trait. LÄS MER

3. 12. Synthesis of Tabular Financial Data using Generative Adversarial Networks

   Master-uppsats, KTH/Matematisk statistik

   Författare :Anton Karlsson; Torbjörn Sjöberg; [2020]
   Nyckelord :Generative Adversarial Networks; GAN; Generative Modeling; Tabular data; Financial data; Machine Learning; Statistical learning; Applied Mathematics; GANs; Generativa modeller; Tabulär data; Finansdata; Maskininlärning; Statistisk inlärning; Tillämpad Matematik;

   Sammanfattning : Digitalization has led to tons of available customer data and possibilities for data-driven innovation. However, the data needs to be handled carefully to protect the privacy of the customers. Generative Adversarial Networks (GANs) are a promising recent development in generative modeling. LÄS MER

4. 13. Early-Stage Prediction of Lithium-Ion Battery Cycle Life Using Gaussian Process Regression

   Master-uppsats, KTH/Matematisk statistik

   Författare :Love Wikland; [2020]
   Nyckelord :Statistical learning; prediction; regression; Gaussian processes; lithium-ion battery; battery health; battery lifetime; Statistisk inlärning; prediction; regression; Gaussiska processer; litiumjonbatteri; batterihälsa; batterilivstid;

   Sammanfattning : Data-driven prediction of battery health has gained increased attention over the past couple of years, in both academia and industry. Accurate early-stage predictions of battery performance would create new opportunities regarding production and use. LÄS MER

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

   Master-uppsats, KTH/Matematisk statistik

   Författare :Mattias Gullstrand; Stefan Maraš; [2020]
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

7. 15. One-shot learning through generalized representations with neural networks

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

   Författare :Paul Vinell; Adam Wiker; [2020]
   Nyckelord :;

   Sammanfattning : Despite the rapid progress in the field of machine learning and artificial neural networks, many hurdles yet remain before machines can match human capabilities. One such hurdle is the copious amount of data required for these learning machines to reach adequate performance. LÄS MER