Stefan Schrunner

About Stefan Schrunner

Stefan Schrunner, With an exceptional h-index of 6 and a recent h-index of 6 (since 2020), a distinguished researcher at Norges miljø- og biovitenskapelige universitet, specializes in the field of Statistics, Data Science, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

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

Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science

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

UBayFS: An R package for user guided feature selection

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

A Gaussian Sliding Windows Regression Model for Hydrological Inference

Component Based Pre-filtering of Noisy Data for Improved Tsetlin Machine Modelling

Ranking Feature-Block Importance in Artificial Multiblock Neural Networks

Stefan Schrunner Information

University

Position

(NMBU)

Citations(all)

134

Citations(since 2020)

130

Cited By

30

hIndex(all)

6

hIndex(since 2020)

6

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Norges miljø- og biovitenskapelige universitet

Google Scholar

View Google Scholar Profile

Stefan Schrunner Skills & Research Interests

Statistics

Data Science

Machine Learning

Top articles of Stefan Schrunner

Title

Journal

Author(s)

Publication Date

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

Computer Methods and Programs in Biomedicine

Anna Jenul

Henning Langen Stokmo

Stefan Schrunner

Geir Olav Hjortland

Mona-Elisabeth Revheim

...

2024/2/1

Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science

arXiv preprint arXiv:2303.06501

Joseph Janssen

Shizhe Meng

Asad Haris

Stefan Schrunner

Jiguo Cao

...

2023/3/11

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

arXiv preprint arXiv:2302.10106

Anna Jenul

Henning Langen Stokmo

Stefan Schrunner

Mona-Elisabeth Revheim

Geir Olav Hjortland

...

2023/2/20

UBayFS: An R package for user guided feature selection

Journal of Open Source Software

Anna Jenul

Stefan Schrunner

2023/1/27

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

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization

Delmon Arous

Stefan Schrunner

Ingunn Hanson

Nina Frederike Jeppesen Edin

Eirik Malinen

2023/1/2

A Gaussian Sliding Windows Regression Model for Hydrological Inference

arXiv preprint arXiv:2306.00453

Stefan Schrunner

Joseph Janssen

Anna Jenul

Jiguo Cao

Ali A Ameli

...

2023/6/1

Component Based Pre-filtering of Noisy Data for Improved Tsetlin Machine Modelling

Anna Jenul

Bimal Bhattarai

Kristian Hovde Liland

Lei Jiao

Stefan Schrunner

...

2022/6/20

Ranking Feature-Block Importance in Artificial Multiblock Neural Networks

Anna Jenul

Stefan Schrunner

Bao Ngoc Huynh

Runar Helin

Cecilia Marie Futsæther

...

2022/9/6

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

Machine Learning

Anna Jenul

Stefan Schrunner

Jürgen Pilz

Oliver Tomic

2022/10

Rent—repeated elastic net technique for feature selection

IEEE Access

Anna Jenul

Stefan Schrunner

Kristian Hovde Liland

Ulf Geir Indahl

Cecilia Marie Futsæther

...

2021/11/8

RENT: A Python package for repeated elastic net feature selection

Journal of Open Source Software

Anna Jenul

Stefan Schrunner

Bao Ngoc Huynh

Oliver Tomic

2021/7/28

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

CoRR

Stefan Schrunner

Michael Scheiber

Anna Jenul

Anja Zernig

Andre Kaestner

...

2021/3/25

Towards a General Framework to Embed Advanced Machine Learning in Process Control Systems

arXiv preprint arXiv:2103.13058

Stefan Schrunner

Michael Scheiber

Anna Jenul

Anja Zernig

Andre Kästner

...

2021/3/24

A generative semi-supervised classifier for datasets with unknown classes

Stefan Schrunner

Bernhard C Geiger

Anja Zernig

Roman Kern

2020/3/30

An explicit solution for image restoration using Markov random fields

Journal of Signal Processing Systems

Martin Pleschberger

Stefan Schrunner

Jürgen Pilz

2020/2

See List of Professors in Stefan Schrunner University(Norges miljø- og biovitenskapelige universitet)

Co-Authors

H-index: 31
Eirik Malinen

Eirik Malinen

Universitetet i Oslo

H-index: 29
Ulf G. Indahl

Ulf G. Indahl

Norges miljø- og biovitenskapelige universitet

H-index: 29
Kristian Hovde Liland

Kristian Hovde Liland

Norges miljø- og biovitenskapelige universitet

H-index: 28
Jiguo Cao

Jiguo Cao

Simon Fraser University

H-index: 26
Oliver Tomic

Oliver Tomic

Norges miljø- og biovitenskapelige universitet

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