Drift Detection in Text Data with Document Embeddings. - Robert Feldhans; Adrian Wilke; Stefan Heindorf; Mohammad Hossein Shaker; Barbara Hammer; Axel-Cyrille Ngonga Ngomo; Eyke Hüllermeier (IDEAL, 2021)

Contrastive Explanations for Explaining Model Adaptations. - André Artelt; Fabian Hinder; Valerie Vaquet; Robert Feldhans; Barbara Hammer (IWANN (1), 2021)

Evaluating Metrics for Bias in Word Embeddings. - Sarah Schröder; Alexander Schulz 001; Philip Kenneweg; Robert Feldhans; Fabian Hinder; Barbara Hammer (CoRR, 2021)

The SAME score: Improved cosine based bias score for word embeddings. - Sarah Schröder; Alexander Schulz 001; Philip Kenneweg; Robert Feldhans; Fabian Hinder; Barbara Hammer (CoRR, 2022)

Measuring Fairness with Biased Data: A Case Study on the Effects of Unsupervised Data in Fairness Evaluation. - Sarah Schröder; Alexander Schulz 001; Ivan Tarakanov; Robert Feldhans; Barbara Hammer (IWANN (1), 2023)

Data Augmentation for Cardiovascular Time Series Data Using WaveNet. - Robert Feldhans; Alexander Schulz 001; Johannes Kummert; Moriz Habigt; Maike Stemmler; Christina Kohler; Dirk Abel; Rolf Rossaint; Barbara Hammer (SSCI, 2023)

Generating Cardiovascular Data to Improve Training of Assistive Heart Devices. - Johannes Kummert; Alexander Schulz 001; Robert Feldhans; Moriz Habigt; Maike Stemmler; Christina Kohler; Dirk Abel; Rolf Rossaint; Barbara Hammer (SSCI, 2023)

Contrasting Explanations for Understanding and Regularizing Model Adaptations. - André Artelt; Fabian Hinder; Valerie Vaquet; Robert Feldhans; Barbara Hammer (Neural Process. Lett., 2023)

Towards Reliable Drift Detection and Explanation in Text Data. - Robert Feldhans; Barbara Hammer (IDEAL (1), 2024)