Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. - Marek Herde; Daniel Kottke; Adrian Calma; Maarten Bieshaar; Stephan Deist; Bernhard Sick (IJCNN, 2018)

Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. - Christoph Sandrock; Marek Herde; Adrian Calma; Daniel Kottke; Bernhard Sick (IJCNN, 2019)

Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. - Tom Hanika; Marek Herde; Jochen Kuhn; Jan Marco Leimeister; Paul Lukowicz; Sarah Oeste-Reiß; Albrecht Schmidt 001; Bernhard Sick; Gerd Stumme; Sven Tomforde; Katharina Anna Zweig (CoRR, 2019)

Multi-Annotator Probabilistic Active Learning. - Marek Herde; Daniel Kottke; Denis Huseljic; Bernhard Sick (ICPR, 2020)

Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. - Denis Huseljic; Bernhard Sick; Marek Herde; Daniel Kottke (ICPR, 2020)

A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. - Maarten Bieshaar; Marek Herde; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2021)

A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. - Marek Herde; Denis Huseljic; Bernhard Sick; Adrian Calma (IEEE Access, 2021)

Toward optimal probabilistic active learning using a Bayesian approach. - Daniel Kottke; Marek Herde; Christoph Sandrock; Denis Huseljic; Georg Krempl; Bernhard Sick (Mach. Learn., 2021)

A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning. - Marek Herde; Denis Huseljic; Jelena Mitrovic; Michael Granitzer; Bernhard Sick (IAL@PKDD/ECML, 2022)

A Review of Uncertainty Calibration in Pretrained Object Detectors. - Denis Huseljic; Marek Herde; Mehmet Muejde; Bernhard Sick (CoRR, 2022)

Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. - Marek Herde; Zhixin Huang; Denis Huseljic; Daniel Kottke; Stephan Vogt; Bernhard Sick (CoRR, 2022)

Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. - Christoph Sandrock; Marek Herde; Daniel Kottke; Bernhard Sick (DS, 2023)

Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning. - Marek Herde; Denis Huseljic; Bernhard Sick; Ulrich Bretschneider; Sarah Oeste-Reiß (IAL@PKDD/ECML, 2023)

Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. - Zhixin Huang; Yujiang He; Marek Herde; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2023)

Role of Hyperparameters in Deep Active Learning. - Denis Huseljic; Marek Herde; Paul Hahn; Bernhard Sick (IAL@PKDD/ECML, 2023)

Active Label Refinement for Semantic Segmentation of Satellite Images. - Tuan Pham Minh; Jayan Wijesingha; Daniel Kottke; Marek Herde; Denis Huseljic; Bernhard Sick; Michael Wachendorf; Thomas Esch (CoRR, 2023)

Multi-annotator Deep Learning: A Probabilistic Framework for Classification. - Marek Herde; Denis Huseljic; Bernhard Sick (Trans. Mach. Learn. Res., 2023)

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. - Marek Herde; Lukas Lührs; Denis Huseljic; Bernhard Sick (ECAI, 2024)

General Reusability: Ensuring Long-Term Benefits of Deep Active Learning. - Paul Hahn; Denis Huseljic; Marek Herde; Bernhard Sick (IAL@PKDD/ECML, 2024)

Tutorial: Interactive Adaptive Learning. - Marek Herde; Tuan Pham Minh; Alaa Tharwat; Bernhard Sick (IAL@PKDD/ECML, 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (NeurIPS, 2024)

Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification. - Denis Huseljic; Paul Hahn; Marek Herde; Lukas Rauch; Bernhard Sick (ECML/PKDD (7), 2024)

The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification. - Denis Huseljic; Marek Herde; Yannick Nagel; Lukas Rauch; Paulius Strimaitis; Bernhard Sick (Trans. Mach. Learn. Res., 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (Zenodo, 2024)

dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. - Marek Herde; Denis Huseljic; Lukas Rauch; Bernhard Sick (Zenodo, 2024)

BirdSet: A Large-Scale Dataset for Audio Classification in Avian Bioacoustics. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; René Heinrich; Denis Huseljic; Marek Herde; Jonas Lange; Stefan Kahl; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (ICLR, 2025)

Systematic Evaluation of Uncertainty Calibration in Pretrained Object Detectors. - Denis Huseljic; Marek Herde; Paul Hahn; Mehmet Muejde; Bernhard Sick (Int. J. Comput. Vis., 2025)

crowd-hpo: Realistic Hyperparameter Optimization and Benchmarking for Learning from Crowds with Noisy Labels. - Marek Herde; Lukas Lührs; Denis Huseljic; Bernhard Sick (CoRR, 2025)

No Free Lunch in Active Learning: LLM Embedding Quality Dictates Query Strategy Success. - Lukas Rauch; Moritz Wirth; Denis Huseljic; Marek Herde; Bernhard Sick; Matthias Aßenmacher (CoRR, 2025)