| Rent—repeated elastic net technique for feature selection A Jenul, S Schrunner, KH Liland, UG Indahl, CM Futsæther, O Tomic IEEE Access 9, 152333-152346, 2021 | 33 | 2021 |
| Feature extraction from analog wafermaps: A comparison of classical image processing and a deep generative model T Santos, S Schrunner, BC Geiger, O Pfeiler, A Zernig, A Kaestner, R Kern IEEE Transactions on Semiconductor Manufacturing 32 (2), 190-198, 2019 | 27 | 2019 |
| RENT: A Python package for repeated elastic net feature selection A Jenul, S Schrunner, BN Huynh, O Tomic Journal of Open Source Software 6 (63), 3323, 2021 | 14 | 2021 |
| A comparison of supervised approaches for process pattern recognition in analog semiconductor wafer test data S Schrunner, O Bluder, A Zernig, A Kaestner, R Kern 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 12 | 2018 |
| A generative semi-supervised classifier for datasets with unknown classes S Schrunner, BC Geiger, A Zernig, R Kern Proceedings of the 35th Annual ACM Symposium on Applied Computing, 1066-1074, 2020 | 10 | 2020 |
| A user-guided Bayesian framework for ensemble feature selection in life science applications (UBayFS) A Jenul, S Schrunner, J Pilz, O Tomic Machine Learning, 2022 | 9 | 2022 |
| An explicit solution for image restoration using Markov random fields M Pleschberger, S Schrunner, J Pilz Journal of Signal Processing Systems 92 (2), 257-267, 2020 | 9 | 2020 |
| A health factor for process patterns enhancing semiconductor manufacturing by pattern recognition in analog wafermaps S Schrunner, A Jenul, M Scheiber, A Zernig, A Kaestner, R Kern 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC …, 2019 | 6 | 2019 |
| Pattern Recognition in Analog Wafer Test Data - A Health Factor for Process Patterns S Schrunner Graz University of Technology, 2019 | 5 | 2019 |
| Markov random fields for pattern extraction in analog wafer test data S Schrunner, O Bluder, A Zernig, A Kaestner, R Kern 2017 Seventh International Conference on Image Processing Theory, Tools and …, 2017 | 5 | 2017 |
| Simulated analog wafer test data for pattern recognition M Pleschberger, M Scheiber, S Schrunner Google Scholar Google Scholar Cross Ref Cross Ref, 2019 | 4 | 2019 |
| UBayFS: An R package for user guided feature selection A Jenul, S Schrunner Journal of Open Source Software 8 (81), 4848, 2023 | 2 | 2023 |
| Principal component-based image segmentation: a new approach to outline in vitro cell colonies D Arous, S Schrunner, I Hanson, N Frederike Jeppesen Edin, E Malinen Computer Methods in Biomechanics and Biomedical Engineering: Imaging …, 2023 | 2 | 2023 |
| Ranking Feature-Block Importance in Artificial Multiblock Neural Networks A Jenul, S Schrunner, BN Huynh, R Helin, CM Futsæther, KH Liland, ... International Conference on Artificial Neural Networks, 163-175, 2022 | 2 | 2022 |
| Learning from limited temporal data: Dynamically sparse historical functional linear models with applications to Earth science J Janssen, S Meng, A Haris, S Schrunner, J Cao, WJ Welch, N Kunz, ... arXiv preprint arXiv:2303.06501, 2023 | 1 | 2023 |
| Multiblock-Networks: A Neural Network Analog to Component Based Methods for Multi-Source Data A Jenul, S Schrunner, R Helin, KH Liland, CM Futsaether, O Tomic arXiv preprint arXiv:2109.10279, 2021 | 1 | 2021 |
| Novel ensemble feature selection techniques applied to high-grade gastroenteropancreatic neuroendocrine neoplasms for the prediction of survival A Jenul, HL Stokmo, S Schrunner, GO Hjortland, ME Revheim, O Tomic Computer Methods and Programs in Biomedicine 244, 107934, 2024 | | 2024 |
| A Gaussian Sliding Windows Regression Model for Hydrological Inference S Schrunner, J Janssen, A Jenul, J Cao, AA Ameli, WJ Welch arXiv preprint arXiv:2306.00453, 2023 | | 2023 |
| Towards Understanding the Survival of Patients with High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms: An Investigation of Ensemble Feature Selection in the Prediction … A Jenul, HL Stokmo, S Schrunner, ME Revheim, GO Hjortland, O Tomic arXiv preprint arXiv:2302.10106, 2023 | | 2023 |
| Component Based Pre-filtering of Noisy Data for Improved Tsetlin Machine Modelling A Jenul, B Bhattarai, KH Liland, L Jiao, S Schrunner, C Futsaether, ... 2022 International Symposium on the Tsetlin Machine (ISTM), 57-64, 2022 | | 2022 |
Roman KernKnow Center, Graz University of Technology在 know-center.at 的电子邮件经过验证
