33 citations · 57 across the 6 of their papers we have counts for
6 papers
A Gaussian Sliding Windows Regression Model for Hydrological Inference
Stefan Schrunner, Parham Pishrobat, Joseph Janssen +4
Statistical models are an essential tool to model, forecast and understand the hydrological processes in watersheds. In particular, the understanding of time lags associated with t…
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 +3
Determining the most informative features for predicting the overall survival of patients diagnosed with high-grade gastroenteropancreatic neuroendocrine neoplasms is crucial to im…
Ranking Feature-Block Importance in Artificial Multiblock Neural Networks
Anna Jenul, Stefan Schrunner, Bao Ngoc Huynh +4
In artificial neural networks, understanding the contributions of input features on the prediction fosters model explainability and delivers relevant information about the dataset.…
A User-Guided Bayesian Framework for Ensemble Feature Selection in Life Science Applications (UBayFS)
Anna Jenul, Stefan Schrunner, Jürgen Pilz +1
Feature selection represents a measure to reduce the complexity of high-dimensional datasets and gain insights into the systematic variation in the data. This aspect is of specific…
Towards a General Framework to Embed Advanced Machine Learning in Process Control Systems
Stefan Schrunner, Michael Scheiber, Anna Jenul +3
Since high data volume and complex data formats delivered in modern high-end production environments go beyond the scope of classical process control systems, more advanced tools i…
RENT -- Repeated Elastic Net Technique for Feature Selection
Anna Jenul, Stefan Schrunner, Kristian Hovde Liland +3
Feature selection is an essential step in data science pipelines to reduce the complexity associated with large datasets. While much research on this topic focuses on optimizing pr…