| Evaluating metrics for bias in word embeddings S Schröder, A Schulz, P Kenneweg, R Feldhans, F Hinder, B Hammer arXiv preprint arXiv:2111.07864, 2021 | 9 | 2021 |
| Contrastive explanations for explaining model adaptations A Artelt, F Hinder, V Vaquet, R Feldhans, B Hammer International Work-Conference on Artificial Neural Networks, 101-112, 2021 | 7 | 2021 |
| Drift detection in text data with document embeddings R Feldhans, A Wilke, S Heindorf, MH Shaker, B Hammer, ... Intelligent Data Engineering and Automated Learning–IDEAL 2021: 22nd …, 2021 | 7 | 2021 |
| Contrasting explanations for understanding and regularizing model adaptations A Artelt, F Hinder, V Vaquet, R Feldhans, B Hammer Neural Processing Letters 55 (5), 5273-5297, 2023 | 4 | 2023 |
| The same score: Improved cosine based bias score for word embeddings S Schröder, A Schulz, P Kenneweg, R Feldhans, F Hinder, B Hammer arXiv preprint arXiv:2203.14603, 2022 | 1 | 2022 |
| Generating Cardiovascular Data to Improve Training of Assistive Heart Devices J Kummert, A Schulz, R Feldhans, M Habigt, M Stemmler, C Kohler, ... 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 1292-1297, 2023 | | 2023 |
| Data Augmentation for Cardiovascular Time Series Data Using WaveNet R Feldhans, A Schulz, J Kummert, M Habigt, M Stemmler, C Kohler, ... 2023 IEEE Symposium Series on Computational Intelligence (SSCI), 836-841, 2023 | | 2023 |
| Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation S Schröder, A Schulz, I Tarakanov, R Feldhans, B Hammer International Work-Conference on Artificial Neural Networks, 134-145, 2023 | | 2023 |
| EML4U-Erklärbares Maschinelles Lernen für interaktive episodische Updates von Modellen: Schlussbericht: Forschungsvorhaben zur Weiterentwicklung von Methoden im Bereich der … B Hammer, E Hüllermeier, ACN Ngomo, M Hartung, R Feldhans, ... Universität Bielefeld-Institut für Kognition und Robotik (CoR-Lab); Machine …, 2023 | | 2023 |
