214 citations
- University of OsloNO22 papers
- Forschungszentrum JülichDE16 papers
- Instituto Nacional de Pesquisas EspaciaisBR10 papers
- Jülich Aachen Research AllianceDE10 papers
- Petersburg Nuclear Physics InstituteRU10 papers
- Norwegian University of Science and TechnologyNO9 papers
- RWTH Aachen UniversityDE8 papers
- University of California, RiversideUS8 papers
- Simula Research LaboratoryNO7 papers
- SINTEFNO6 papers
- Karlsruhe Institute of TechnologyDE5 papers
- The University of Texas at AustinUS5 papers
6 papers · 1 filter
Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations
Berk Hadzhamolla, Alexander Johannes Stasik, Signe Riemer-Sørensen
Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operation. Numerical approaches suc…
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.…
Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods
Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani +9
The first known case of Coronavirus disease 2019 (COVID-19) was identified in December 2019. It has spread worldwide, leading to an ongoing pandemic, imposed restrictions and costs…
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…
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…