Unification of Deconvolution Algorithms for Cherenkov Astronomy. - Mirko Bunse; Nico Piatkowski; Katharina Morik; Tim Ruhe; Wolfgang Rhode (DSAA, 2018)

Towards a Unifying View on Deconvolution in Cherenkov Astronomy. - Mirko Bunse; Nico Piatkowski; Katharina Morik (LWDA, 2018)

A Data Science Perspective on Deconvolution. - Mirko Bunse; Nico Piatkowski; Tim Ruhe; Katharina Morik; Wolfgang Rhode (GI-Jahrestagung, 2019)

What Can We Expect from Active Class Selection? - Mirko Bunse; Katharina Morik (LWDA, 2019)

Optimal Probabilistic Classification in Active Class Selection. - Mirko Bunse; Dorina Weichert; Alexander Kister; Katharina Morik (ICDM, 2020)

Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots. - Nikolaos Nikolaou; Ingo P. Waldmann; Angelos Tsiaras; Mario Morvan; Billy Edwards; Kai Hou Yip; Giovanna Tinetti; Subhajit Sarkar; James M. Dawson; Vadim Borisov; Gjergji Kasneci; Matej Petkovic; et al. (CoRR, 2020)

Certification of Model Robustness in Active Class Selection. - Mirko Bunse; Katharina Morik (ECML/PKDD (2), 2021)

Active Class Selection with Uncertain Class Proportions. - Mirko Bunse; Katharina Morik (IAL@PKDD/ECML, 2021)

Noisy Labels for Weakly Supervised Gamma Hadron Classification. - Lukas Pfahler; Mirko Bunse; Katharina Morik (CoRR, 2021)

Key Concepts in Machine Learning and Data Analysis. - Katharina Morik; Mirko Bunse (Mach. Learn. under Resour. Constraints Vol. 2 (2), 2022)

Inverse Problems. - Tim Ruhe; Mirko Bunse; Wolfgang Rhode; Bernhard Spaan; Michael Schmelling; Maximilian Linhoff; Marlene Doert; Karolin Hymon (Mach. Learn. under Resour. Constraints Vol. 2 (2), 2022)

Monte Carlo Simulations. - Bernhard Spaan; Hans Dembinski; Gerwin Meier; Jean-Marco Alameddine; Dominik Baack; Mirko Bunse; Jens Teubner; Thomas Lindemann; Maximilian Linhoff; Tim Ruhe (Mach. Learn. under Resour. Constraints Vol. 2 (2), 2022)

DortmundAI at LeQua 2022: Regularized SLD. - Martin Senz; Mirko Bunse (CLEF (Working Notes), 2022)

Unification of Algorithms for Quantification and Unfolding. - Mirko Bunse (GI-Jahrestagung, 2022)

Ordinal Quantification Through Regularization. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (ECML/PKDD (5), 2022)

Certifiable Active Class Selection in Multi-Class Classification. - Martin Senz; Mirko Bunse; Katharina Morik (IAL@PKDD/ECML, 2022)

Machine learning for acquiring knowledge in astro-particle physics. - Mirko Bunse (2022)

Product Reviews for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2022)

Cherenkov Telescope Data for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2022)

Tutorial: Interactive Adaptive Learning. - Mirko Bunse; Georg Krempl; Alaa Tharwat; Amal Saadallah (IAL@PKDD/ECML, 2023)

Class-Conditional Label Noise in Astroparticle Physics. - Mirko Bunse; Lukas Pfahler (ECML/PKDD (6), 2023)

Cherenkov Telescope Data for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2023)

Product Reviews for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2023)

UCI and OpenML Data Sets for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2023)

Product Reviews for Ordinal Quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Zenodo, 2023)

Report on the 3rd International Workshop onLearning to Quantify (LQ 2023). - Mirko Bunse; Pablo González; Alejandro Moreo; Fabrizio Sebastiani 001 (SIGKDD Explor., 2023)

Regularization-based methods for ordinal quantification. - Mirko Bunse; Alejandro Moreo; Fabrizio Sebastiani 001; Martin Senz (Data Min. Knowl. Discov., 2024)