Stefan Schrunner

According to our database, Stefan Schrunner authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2024

Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival.

Anna Jenul, Henning Langen Stokmo, Stefan Schrunner, Geir Olav Hjortland, Mona-Elisabeth Revheim, Oliver Tomic

Comput. Methods Programs Biomed., 2024

2023

UBayFS: An R Package for User Guided Feature Selection.

Anna Jenul, Stefan Schrunner

J. Open Source Softw., January, 2023

Principal component-based image segmentation: a new approach to outline <i>in vitro</i> cell colonies.

Delmon Arous, Stefan Schrunner, Ingunn Hanson, Nina Frederike Jeppesen Edin, Eirik Malinen

Comput. methods Biomech. Biomed. Eng. Imaging Vis., January, 2023

Towards Understanding the Survival of Patients with High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms: An Investigation of Ensemble Feature Selection in the Prediction of Overall Survival.

Anna Jenul, Henning Langen Stokmo, Stefan Schrunner, Mona-Elisabeth Revheim, Geir Olav Hjortland, Oliver Tomic

CoRR, 2023

2022

A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS).

Anna Jenul, Stefan Schrunner, Jürgen Pilz, Oliver Tomic

Mach. Learn., 2022

Ranking Feature-Block Importance in Artificial Multiblock Neural Networks.

Anna Jenul, Stefan Schrunner, Bao-Ngoc Huynh, Runar Helin, Cecilia Marie Futsaether, Kristian Hovde Liland, Oliver Tomic

Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021

RENT: A Python Package for Repeated Elastic Net Feature Selection.

Anna Jenul, Stefan Schrunner, Bao Huynh, Oliver Tomic

J. Open Source Softw., 2021

Multiblock-Networks: A Neural Network Analog to Component Based Methods for Multi-Source Data.

Anna Jenul, Stefan Schrunner, Runar Helin, Kristian Hovde Liland, Cecilia Marie Futsaether, Oliver Tomic

CoRR, 2021

Machine Learning based Indicators to Enhance Process Monitoring by Pattern Recognition.

Stefan Schrunner, Michael Scheiber, Anna Jenul, Anja Zernig, Andre Kästner, Roman Kern

CoRR, 2021

Principal component-based image segmentation: a new approach to outline in vitro cell colonies.

Delmon Arous, Stefan Schrunner, Ingunn Hanson, Nina Frederike Jeppesen Edin, Eirik Malinen

CoRR, 2021

RENT - Repeated Elastic Net Technique for Feature Selection.

Anna Jenul, Stefan Schrunner, Kristian Hovde Liland, Ulf Geir Indahl, Cecilia Marie Futsaether, Oliver Tomic

IEEE Access, 2021

2020

An Explicit Solution for Image Restoration using Markov Random Fields.

Martin Pleschberger, Stefan Schrunner, Jürgen Pilz

J. Signal Process. Syst., 2020

A generative semi-supervised classifier for datasets with unknown classes.

Stefan Schrunner, Bernhard C. Geiger, Anja Zernig, Roman Kern

Proceedings of the SAC '20: The 35th ACM/SIGAPP Symposium on Applied Computing, online event, [Brno, Czech Republic], March 30, 2020

2019

A Health Factor for Process Patterns Enhancing Semiconductor Manufacturing by Pattern Recognition in Analog Wafermaps.

Stefan Schrunner, Anna Jenul, Michael Scheiber, Anja Zernig, Andre Kästner, Roman Kern

Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics, 2019

2018

A Comparison of Supervised Approaches for Process Pattern Recognition in Analog Semiconductor Wafer Test Data.

Stefan Schrunner, Olivia Bluder, Anja Zernig, Andre Kästner, Roman Kern

Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

2017

Markov random fields for pattern extraction in analog wafer test data.

Stefan Schrunner, Olivia Bluder, Anja Zernig, Andre Kästner, Roman Kern

Proceedings of the Seventh International Conference on Image Processing Theory, 2017