activity
20242026
collaborators

5 papers

eess.SP2026

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules

Emil Hardarson, Konstantin Popov, Sigridur Sigurdardottir +3

Automated sleep staging is commonly approached as a supervised machine learning problem, with deep learning methods dominating recent research. While machine learning models achiev…

cs.LG2026

Tabular Foundation Models for Credit Risk Prediction: A Dedicated Review and Empirical Comparison

Bart Baesens, Andreas Goethals, Stefan Lessmann +10

Predictive models are central to credit risk management, where the accuracy of default-probability and loss estimates affects the profitability of lending and the stability of the…

cs.LG2026

Data-Local Autonomous LLM-Guided Neural Architecture Search for Multiclass Multimodal Time-Series Classification

Emil Hardarson, Luka Biedebach, Ómar Bessi Ómarsson +3

Applying machine learning to sensitive time-series data is often bottlenecked by the iteration loop: Performance depends strongly on preprocessing and architecture, yet training of…

cs.LG2025

Chaos into Order: Neural Framework for Expected Value Estimation of Stochastic Partial Differential Equations

Ísak Pétursson, María Óskarsdóttir

Stochastic partial differential equations (SPDEs) describe the evolution of random processes over space and time, but their solutions are often analytically intractable and computa…

q-fin.ST2024

Generalized Distribution Prediction for Asset Returns

Ísak Pétursson, María Óskarsdóttir

We present a novel approach for predicting the distribution of asset returns using a quantile-based method with Long Short-Term Memory (LSTM) networks. Our model is designed in two…