Christoph Molnar
Orcid: 0000-0003-2331-868X
According to our database1,
Christoph Molnar
authored at least 17 papers
between 2018 and 2024.
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Bibliography
2024
Scientific Inference with Interpretable Machine Learning: Analyzing Models to Learn About Real-World Phenomena.
Minds Mach., September, 2024
2023
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
Proceedings of the Explainable Artificial Intelligence, 2023
2022
2021
Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
CoRR, 2021
2020
Model-agnostic Feature Importance and Effects with Dependent Features - A Conditional Subgroup Approach.
CoRR, 2020
Proceedings of the Parallel Problem Solving from Nature - PPSN XVI, 2020
Proceedings of the ECML PKDD 2020 Workshops, 2020
Proceedings of the 25th International Conference on Pattern Recognition, 2020
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
Proceedings of the xxAI - Beyond Explainable AI, 2020
Proceedings of the xxAI - Beyond Explainable AI, 2020
2019
Quantifying Interpretability of Arbitrary Machine Learning Models Through Functional Decomposition.
CoRR, 2019
Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
Quantifying Model Complexity via Functional Decomposition for Better Post-hoc Interpretability.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019
2018
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018