# Master theses

## The 50 most recent M.Sc. theses supervised by members of the division

[1]

[2]

[3]

[4]

[5]

[6]

[7]

[8]

H. Essinger and A. Kivelä,
"Object Based Image Retrieval Using Feature Maps of a YOLOv5 Network,"
, 2022.

[9]

[10]

F. Fenoaltea,
"Reliability Based Classification of Transitions in Complex Semi-Markov Models,"
, 2022.

[11]

M. Kazi and N. Stanojlovic,
"Deep Learning Approach for Time- to-Event Modeling of Credit Risk,"
, 2022.

[12]

[13]

L. Börthas and J. Krange Sjölander,
"Machine Learning Based Prediction and Classification for Uplift Modeling,"
, 2020.

[14]

A. Prastorfer,
"Simulation-Based Portfolio Optimization with Coherent Distortion Risk Measures,"
, 2020.

[15]

[16]

T. Charitidis,
"Sequence Prediction for Identifying User Equipment Patterns in Mobile Networks,"
, 2020.

[17]

[18]

S. Kornfeld,
"Predicting Default Probability in Credit Risk using Machine Learning Algorithms,"
, 2020.

[19]

A. Andersson and S. Mirkhani,
"Portfolio Performance Optimization Using Multivariate Time Series Volatilities Processed With Deep Layering LSTM Neurons and Markowitz,"
, 2020.

[20]

[21]

[22]

[23]

S. Ahlqvist and M. Arriaza-Hult,
"How to measure the degree of PIT-ness in a credit rating system for a low default portfolio?,"
, 2020.

[24]

[25]

[26]

[27]

J. Lindberg and I. Wolfert Källman,
"Vehicle Collision Risk Prediction Using a Dynamic Bayesian Network,"
, 2020.

[28]

D. Evholt and O. Larsson,
"Generative Adversarial Networks and Natural Language Processing for Macroeconomic Forecasting,"
, 2020.

[29]

C. Herron and A. Zachrisson,
"Machine Learning Based Intraday Calibration of End of Day Implied Volatility Surfaces,"
, 2020.

[30]

A. Qader and W. Shiver,
"Developing an Advanced Internal Ratings-Based Model by Applying Machine Learning,"
, 2020.

[31]

[32]

P. Hanna and E. Swartling,
"Anomaly Detection in Time Series Data using Unsupervised Machine Learning Methods: A Clustering-Based Approach,"
, 2020.

[33]

[34]

A. Karlsson and T. Sjöberg,
"Synthesis of Tabular Financial Data using Generative Adversarial Networks,"
, 2020.

[35]

[36]

[37]

[38]

[39]

[40]

[41]

[42]

[43]

[44]

[45]

[46]

E. Hendey Bröte,
"Duration-Weighted Carbon Footprint Metrics and Carbon Risk Factor for Credit Portfolios,"
, 2020.

[47]

[48]

R. Spånberg and B. Wallander,
"Swedish Interest Rate Curve Dynamics Using Artificial Neural Networks,"
, 2020.

[49]

[50]

E. Backman and D. Petersson,
"Evaluation of methods for quantifying returns within the premium pension,"
, 2020.

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Belongs to: Mathematical Statistics

Last changed: Feb 24, 2021