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Gunnar König
Gunnar König
Postdoctoral Researcher, University of Tübingen
Bestätigte E-Mail-Adresse bei uni-tuebingen.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
General pitfalls of model-agnostic interpretation methods for machine learning models
C Molnar, G König, J Herbinger, T Freiesleben, S Dandl, CA Scholbeck, ...
International Workshop on Extending Explainable AI Beyond Deep Models and …, 2022
269*2022
Model-agnostic Feature Importance and Effects with Dependent Features--A Conditional Subgroup Approach
C Molnar, G König, B Bischl, G Casalicchio
Data Mining and Knowledge Discovery, 2023
1032023
Relating the partial dependence plot and permutation feature importance to the data generating process
G König*, C Molnar*, T Freiesleben*, J Herbinger, T Reisinger, ...
XAI 2023, 456-479, 2023
892023
Relative Feature Importance
G König, C Molnar, B Bischl, M Grosse-Wentrup
ICPR 2020, 9318--9325, 2021
782021
Scientific inference with interpretable machine learning: Analyzing models to learn about real-world phenomena
T Freiesleben, G König, C Molnar, A Tejero-Cantero
Minds and Machines, 2024
252024
A Causal Perspective on Meaningful and Robust Algorithmic Recourse
G König, T Freiesleben, M Grosse-Wentrup
ICML 2021 Workshop on Algorithmic Recourse; arXiv:2107.07853, 2021
222021
Improvement-Focused Causal Recourse (ICR)
G König, T Freiesleben, M Grosse-Wentrup
AAAI 2023, 2023
212023
Dear XAI community, we need to talk! Fundamental misconceptions in current XAI research
T Freiesleben, G König
XAI 2023, 48-65, 2023
202023
Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)
G König, T Freiesleben, B Bischl, G Casalicchio, M Grosse-Wentrup
arXiv preprint arXiv:2106.08086, 2021
62021
CountARFactuals--Generating plausible model-agnostic counterfactual explanations with adversarial random forests
G König*, S Dandl*, K Blesch*, T Freiesleben*, J Kapar, B Bischl, ...
XAI 2024, 2024
3*2024
Efficient SAGE Estimation via Causal Structure Learning
G König*, C Luther*, M Grosse-Wentrup
AISTATS 2023, 2023
3*2023
If interpretability is the answer, what is the question?: a causal perspective
G König
Dissertation, München, Ludwig-Maximilians-Universität, 2023, 2023
12023
Deep Learning in Objective Classification of Spontaneous Movement of Patients with Parkinson’s Disease Using Large-Scale Free-Living Sensor Data
F Pfister, D Kulić, T Um, D Pichler, A Ahmadi, M Lang, G König, F Achilles, ...
12017
Disentangling Interactions and Dependencies in Feature Attribution
G König*, E Günther*, U von Luxburg
arXiv preprint arXiv:2410.23772, 2024
2024
A Causal Perspective on Challenges for AI in Precision Medicine
G König, M Grosse-Wentrup
Proceedings of the 2nd International Congress on Precision Medicine (PMBC), 2019
2019
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