Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources. - Lukas Rauch; Denis Huseljic; Bernhard Sick (IAL@PKDD/ECML, 2022)

Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering. - Matthias Aßenmacher; Lukas Rauch; Jann Goschenhofer; Andreas Stephan; Bernd Bischl; Benjamin Roth 001; Bernhard Sick (IAL@PKDD/ECML, 2023)

DADO - Low-Cost Query Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (ICMLA, 2023)

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. - Lukas Rauch; Matthias Aßenmacher; Denis Huseljic; Moritz Wirth; Bernd Bischl; Bernhard Sick (ECML/PKDD (1), 2023)

DADO - Low-Cost Selection Strategies for Deep Active Design Optimization. - Jens Decke; Christian Gruhl; Lukas Rauch; Bernhard Sick (CoRR, 2023)

Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (CoRR, 2023)

Towards Deep Active Learning in Avian Bioacoustics. - Lukas Rauch; Denis Huseljic; Moritz Wirth; Jens Decke; Bernhard Sick; Christoph Scholz 001 (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)

BirdSet: A Multi-Task Benchmark for Classification in Avian Bioacoustics. - Lukas Rauch; Raphael Schwinger; Moritz Wirth; René Heinrich; Jonas Lange; Stefan Kahl; Bernhard Sick; Sven Tomforde; Christoph Scholz 001 (CoRR, 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)

AudioProtoPNet: An interpretable deep learning model for bird sound classification. - René Heinrich; Lukas Rauch; Bernhard Sick; Christoph Scholz 001 (Ecol. Informatics, 2025)

Multi-dataset synergistic in supervised learning to pre-label structural components in point clouds from shell construction scenes. - Lukas Rauch; Thomas Braml (CoRR, 2025)

Can Masked Autoencoders Also Listen to Birds? - Lukas Rauch; Ilyass Moummad; René Heinrich; Alexis Joly; Bernhard Sick; Christoph Scholz 001 (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)

Adversarial Training Improves Generalization Under Distribution Shifts in Bioacoustics. - René Heinrich; Lukas Rauch; Bernhard Sick; Christoph Scholz 001 (CoRR, 2025)