Lukas Rauch

According to our database, Lukas Rauch authored at least 11 papers between 2022 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

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

CoRR, 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

CoRR, 2024

Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification.

Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

Towards Deep Active Learning in Avian Bioacoustics.

Lukas Rauch, Denis Huseljic, Moritz Wirth, Jens Decke, Bernhard Sick, Christoph Scholz

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), 2024

2023

Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers.

Lukas Rauch, Raphael Schwinger, Moritz Wirth, Bernhard Sick, Sven Tomforde, Christoph Scholz

CoRR, 2023

DADO - Low-Cost Selection Strategies for Deep Active Design Optimization.

Jens Decke, Christian Gruhl, Lukas Rauch, Bernhard Sick

CoRR, 2023

ActiveGLAE: A Benchmark for Deep Active Learning with Transformers.

Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

DADO - Low-Cost Query Strategies for Deep Active Design Optimization.

Jens Decke, Christian Gruhl, Lukas Rauch, Bernhard Sick

Proceedings of the International Conference on Machine Learning and Applications, 2023

Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering.

Matthias Aßenmacher, Lukas Rauch, Jann Goschenhofer, Andreas Stephan, Bernd Bischl, Benjamin Roth, Bernhard Sick

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2023), 2023

2022

Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources.

Lukas Rauch, Denis Huseljic, Bernhard Sick

Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2022), 2022