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Mathematical Statistics

Master theses

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

[1]
J. Stymne, "Self-Play Reinforcement Learning for Finding Intrusion Prevention Strategies," , 2022.
[2]
D. Thinsz, "Properties of Discrete Laplacians With Application on Brain Networks," , 2022.
[3]
B. Lu, "Prediction of Short-term Default Probability of Credit Card Invoices Using Behavioural Data," , 2022.
[4]
B. Wehlin, "Approximating Quasistationary Distributions Using Deep Learning," , 2022.
[5]
O. Nordström, "Unstructured pruning of pre-trained language models tuned for sentiment classification.," , 2022.
[6]
J. Risberg, "Basil-GAN," , 2022.
[7]
Y. Shao, "Data-driven Discovery of Real-time Road Compaction Parameters," , 2022.
[8]
H. Essinger and A. Kivelä, "Object Based Image Retrieval Using Feature Maps of a YOLOv5 Network," , 2022.
[9]
A. Skärbo Jonsson, "Efficient Music Thumbnailing for Genre Classification," , 2022.
[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]
F. Bragone, "Physics-Informed Machine Learning in Power Transformer Dynamic Thermal Modelling," , 2021.
[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]
W. Löfgren, "Distributional Dynamics of Fama-French Factors in European Markets," , 2020.
[16]
T. Charitidis, "Sequence Prediction for Identifying User Equipment Patterns in Mobile Networks," , 2020.
[17]
N. Nayeri, "Option strategies using hybrid Support Vector Regression - ARIMA," , 2020.
[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]
E. Lagerström and M. Magne Schrab, "An Empirical Study of Modern Portfolio Optimization," , 2020.
[21]
C. García Ling, "Graphical Glitch Detection in Video Games Using CNNs," , 2020.
[22]
A. Eskandari, "VAE-clustering of neural signals and their association to cytokines," , 2020.
[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]
D. Olanders, "Optimal Time-Varying Cash Allocation," , 2020.
[25]
O. Bergqvist, "Calibration of Breast Cancer Natural History Models Using Approximate Bayesian Computation," , 2020.
[26]
O. Ungsgård, "Stochastic Modelling of Cash Flows in Private Equity," , 2020.
[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]
S. Berg and V. Elfström, "IRRBB in a Low Interest Rate Environment," , 2020.
[32]
P. Hanna and E. Swartling, "Anomaly Detection in Time Series Data using Unsupervised Machine Learning Methods: A Clustering-Based Approach," , 2020.
[33]
N. Wang, "Spectral Portfolio Optimisation with LSTM Stock Price Prediction," , 2020.
[34]
A. Karlsson and T. Sjöberg, "Synthesis of Tabular Financial Data using Generative Adversarial Networks," , 2020.
[35]
L. Wikland, "Early-Stage Prediction of Lithium-Ion Battery Cycle Life Using Gaussian Process Regression," , 2020.
[36]
O. Åkerström, "Multi-Agent System for Coordinated Defence," , 2020.
[37]
L. Thorstensson, "Clustering Methods as a Recruitment Tool for Smaller Companies," , 2020.
[38]
V. Nilsson, "Prediction of Dose Probability Distributions Using Mixture Density Networks," , 2020.
[39]
G. Norén, "Noise Robustness of Convolutional Autoencoders and Neural Networks for LPI Radar Classification," , 2020.
[40]
M. Jablecka, "Modelling CLV in the Insurance Industry Using Deep Learning Methods," , 2020.
[41]
G. Singh, "Statistical Modeling of Dynamic Risk in Security Systems," , 2020.
[42]
H. Kerek, "Product Similarity Matching for Food Retail using Machine Learning," , 2020.
[43]
A. Djerf, "Valuation of Additional Tier-1 Contingent Convertible Bonds (AT1 CoCo) : Modelling trigger risk in a practical investment setting," , 2020.
[44]
A. V. Chari, "Prediction of Optimal Packaging Solution using Supervised Learning Methods," , 2020.
[45]
T. Brodd, "Modeling the Relation Between Implied and Realized Volatility," , 2020.
[46]
E. Hendey Bröte, "Duration-Weighted Carbon Footprint Metrics and Carbon Risk Factor for Credit Portfolios," , 2020.
[47]
I. Eriksson, "Image Distance Learning for Probabilistic Dose–Volume Histogram and Spatial Dose Prediction in Radiation Therapy Treatment Planning," , 2020.
[48]
R. Spånberg and B. Wallander, "Swedish Interest Rate Curve Dynamics Using Artificial Neural Networks," , 2020.
[49]
R. Sultani, "Rebalancing 2.0-A Macro Approach to Portfolio Rebalancing," , 2020.
[50]
E. Backman and D. Petersson, "Evaluation of methods for quantifying returns within the premium pension," , 2020.
Full list in the KTH publications portal