| Central moment discrepancy (CMD) for domain-invariant representation learning W Zellinger, T Grubinger, E Lughofer, T Natschläger, S Saminger-Platz International Conference on Learning Representations (ICLR), 2017 | 854 | 2017 |
| Wild patterns reloaded: A survey of machine learning security against training data poisoning AE Cinà, K Grosse, A Demontis, S Vascon, W Zellinger, BA Moser, ... ACM Computing Surveys, 2023 | 232 | 2023 |
| Robust unsupervised domain adaptation for neural networks via moment alignment W Zellinger, BA Moser, T Grubinger, E Lughofer, T Natschläger, ... Information Sciences 483, 174-191, 2019 | 126 | 2019 |
| Domain-invariant partial least squares regression R Nikzad-Langerodi, W Zellinger, E Lughofer, S Saminger-Platz Analytical chemistry, 6693-6701, 2018 | 112 | 2018 |
| AI system engineering—key challenges and lessons learned L Fischer, L Ehrlinger, V Geist, R Ramler, F Sobiezky, W Zellinger, ... Machine Learning and Knowledge Extraction 3 (1), 56-83, 2020 | 100 | 2020 |
| Domain adaptation for regression under Beer–Lambert’s law R Nikzad-Langerodi, W Zellinger, S Saminger-Platz, BA Moser Knowledge-Based Systems, 106447, 2020 | 83 | 2020 |
| Mixture density generative adversarial networks H Eghbal-zadeh, W Zellinger, G Widmer IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 5820-5829, 2019 | 53 | 2019 |
| SymbolicAI: A framework for logic-based approaches combining generative models and solvers MC Dinu, C Leoveanu-Condrei, M Holzleitner, W Zellinger, S Hochreiter Conference on Lifelong Learning Agents (CoLLAs), 2024 | 36 | 2024 |
| Multi-source transfer learning of time series in cyclical manufacturing W Zellinger, T Grubinger, M Zwick, E Lughofer, H Schöner, T Natschläger, ... Journal of Intelligent Manufacturing 31, 777-787, 2020 | 36 | 2020 |
| Beyond federated learning: On confidentiality-critical machine learning applications in industry W Zellinger, V Wieser, M Kumar, D Brunner, N Shepeleva, R Gálvez, ... Procedia Computer Science 180, 734-743, 2021 | 33 | 2021 |
| On a regularization of unsupervised domain adaptation in RKHS ER Gizewski, L Mayer, BA Moser, DH Nguyen, S Pereverzyev Jr, ... Applied and Computational Harmonic Analysis 57, 201-227, 2022 | 30 | 2022 |
| Applying AI in practice: key challenges and lessons learned L Fischer, L Ehrlinger, V Geist, R Ramler, F Sobieczky, W Zellinger, ... International Cross-Domain Conference for Machine Learning and Knowledge …, 2020 | 24 | 2020 |
| Addressing parameter choice issues in unsupervised domain adaptation by aggregation MC Dinu, M Holzleitner, M Beck, HD Nguyen, A Huber, H Eghbal-zadeh, ... International Conference on Learning Representations (ICLR, oral talk), 2023 | 22 | 2023 |
| Rethinking data augmentation for adversarial robustness H Eghbal-zadeh, W Zellinger, M Pintor, K Grosse, K Koutini, BA Moser, ... Information Sciences 654, 119838, 2024 | 18 | 2024 |
| On generalization in moment-based domain adaptation W Zellinger, BA Moser, S Saminger-Platz Annals of Mathematics and Artificial Intelligence 89, 333-369, 2021 | 18* | 2021 |
| The balancing principle for parameter choice in distance-regularized domain adaptation W Zellinger, N Shepeleva, MC Dinu, H Eghbal-zadeh, H Nguyen, ... Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 16 | 2021 |
| Domain-invariant regression under Beer-Lambert's law R Nikzad-Langerodi, W Zellinger, S Saminger-Platz, B Moser IEEE ICMLA, 581-586, 2019 | 16 | 2019 |
| On data augmentation and adversarial risk: An empirical analysis H Eghbal-zadeh, K Koutini, P Primus, V Haunschmid, M Lewandowski, ... ICLR Workshop Towards Trustworthy Machine Learning, 2020 | 13 | 2020 |
| Few-shot learning by dimensionality reduction in gradient space M Gauch, M Beck, T Adler, D Kotsur, S Fiel, H Eghbal-zadeh, ... Conference on Lifelong Learning Agents (CoLLAs), 2022 | 12 | 2022 |
| On regularized Radon-Nikodym differentiation DH Nguyen, W Zellinger, SV Pereverzyev Journal of Machine Learning Research 25 (266), 1-24, 2024 | 10 | 2024 |
Bernhard A. MoserSCCH and Institute of Signal Processing, JKU, AustriaVerified email at scch.at
