Ludwig Bothmann

ORCID

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 14

Top Venues

Ludwig Maximilian University of Munich, Germany (PHD)

Education History

Ludwig Maximilian University of Munich, Germany

PHD

Publications

Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer
Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks? CoRR (2024)
Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright, Bernd Bischl, Giuseppe Casalicchio, Gunnar König
A Guide to Feature Importance Methods for Scientific Inference. CoRR (2024)
Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann
mlr3summary: Concise and interpretable summaries for machine learning models. CoRR (2024)
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. CoRR (2023)
Ludwig Bothmann, Susanne Dandl, Michael Schomaker
Causal Fair Machine Learning via Rank-Preserving Interventional Distributions. AEQUITAS@ECAI (2023)
Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber, Hendrik Edelhoff, Wibke Peters, Hien Nguyen, Caryl Benjamin, Annette Menzel
Automated wildlife image classification: An active learning tool for ecological applications. CoRR (2023)
Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber, Hendrik Edelhoff, Wibke Peters, Hien Nguyen, Caryl Benjamin, Annette Menzel
Automated wildlife image classification: An active learning tool for ecological applications. Ecol. Informatics 77 (2023)
Ludwig Bothmann, Susanne Dandl, Michael Schomaker
Causal Fair Machine Learning via Rank-Preserving Interventional Distributions. CoRR (2023)
Roman Hornung, Malte Nalenz, Lennart Schneider, Andreas Bender, Ludwig Bothmann, Bernd Bischl, Thomas Augustin, Anne-Laure Boulesteix
Evaluating machine learning models in non-standard settings: An overview and new findings. CoRR (2023)
Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann
Interpretable Regional Descriptors: Hyperbox-Based Local Explanations. ECML/PKDD (3) (2023)
Wael Ghada, Éric Casellas, Julia Herbinger, Albert Garcia-Benadí, Ludwig Bothmann, Nicole Estrella, Joan Bech, Annette Menzel
Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar. Remote. Sens. 14 (18) (2022)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. Teaching ML (2022)
Ludwig Bothmann, Kristina Peters, Bernd Bischl
What Is Fairness? Implications For FairML. CoRR (2022)
Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl
Developing Open Source Educational Resources for Machine Learning and Data Science. CoRR (2021)

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Publication Activity (10 Years)

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Ludwig Bothmann