Ludwig Bothmann

According to our database, Ludwig Bothmann authored at least 12 papers between 2016 and 2024.

Collaborative distances:

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

2024

Fairness als Qualitätskriterium im Maschinellen Lernen - Rekonstruktion des philosophischen Konzepts und Implikationen für die Nutzung außergesetzlicher Merkmale bei qualifizierten Mietspiegeln.

Ludwig Bothmann, Kristina Peters

AStA Wirtschafts und Sozialstatistisches Arch., June, 2024

A Guide to Feature Importance Methods for Scientific Inference.

Fiona Katharina Ewald, Ludwig Bothmann, Marvin N. Wright, Bernd Bischl, Giuseppe Casalicchio, Gunnar König

Proceedings of the Explainable Artificial Intelligence, 2024

mlr3summary: Concise and interpretable summaries for machine learning models.

Susanne Dandl, Marc Becker, Bernd Bischl, Giuseppe Casalicchio, Ludwig Bothmann

Proceedings of the Joint Proceedings of the xAI 2024 Late-breaking Work, 2024

Connecting the Dots: Is Mode-Connectedness the Key to Feasible Sample-Based Inference in Bayesian Neural Networks?

Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Automated wildlife image classification: An active learning tool for ecological applications.

Ludwig Bothmann, Lisa Wimmer, Omid Charrakh, Tobias Weber, Hendrik Edelhoff, Wibke Peters, Hien Nguyen, Caryl Benjamin, Annette Menzel

Ecol. Informatics, November, 2023

Evaluating machine learning models in non-standard settings: An overview and new findings.

Roman Hornung, Malte Nalenz, Lennart Schneider, Andreas Bender, Ludwig Bothmann, Bernd Bischl, Thomas Augustin, Anne-Laure Boulesteix

CoRR, 2023

Interpretable Regional Descriptors: Hyperbox-Based Local Explanations.

Susanne Dandl, Giuseppe Casalicchio, Bernd Bischl, Ludwig Bothmann

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

Causal Fair Machine Learning via Rank-Preserving Interventional Distributions.

Ludwig Bothmann, Susanne Dandl, Michael Schomaker

Proceedings of the 1st Workshop on Fairness and Bias in AI co-located with 26th European Conference on Artificial Intelligence (ECAI 2023), 2023

2022

Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar.

Wael Ghada, Éric Casellas, Julia Herbinger, Albert Garcia-Benadí, Ludwig Bothmann, Nicole Estrella, Joan Bech, Annette Menzel

Remote. Sens., 2022

What Is Fairness? Implications For FairML.

Ludwig Bothmann, Kristina Peters, Bernd Bischl

CoRR, 2022

Developing Open Source Educational Resources for Machine Learning and Data Science.

Ludwig Bothmann, Sven Strickroth, Giuseppe Casalicchio, David Rügamer, Marius Lindauer, Fabian Scheipl, Bernd Bischl

Proceedings of the Third Teaching Machine Learning and Artificial Intelligence Workshop, 2022

2016

Efficient statistical analysis of video and image data.

Ludwig Bothmann

PhD thesis, 2016