Julia Herbinger

Orcid: 0000-0003-0430-8523

According to our database1, Julia Herbinger authored at least 13 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Effector: A Python package for regional explanations.
CoRR, 2024

Explaining Bayesian Optimization by Shapley Values Facilitates Human-AI Collaboration.
CoRR, 2024

2023
On grouping and partitioning approaches in interpretable machine learning.
PhD thesis, 2023

Decomposing Global Feature Effects Based on Feature Interactions.
CoRR, 2023

Relating the Partial Dependence Plot and Permutation Feature Importance to the Data Generating Process.
Proceedings of the Explainable Artificial Intelligence, 2023

Leveraging Model-Based Trees as Interpretable Surrogate Models for Model Distillation.
Proceedings of the Artificial Intelligence. ECAI 2023 International Workshops - XAI³, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI, Kraków, Poland, September 30, 2023

2022
Stratiform and Convective Rain Classification Using Machine Learning Models and Micro Rain Radar.
Remote. Sens., 2022

Grouped feature importance and combined features effect plot.
Data Min. Knowl. Discov., 2022

Portfolio optimization with optimal expected utility risk measures.
Ann. Oper. Res., 2022

REPID: Regional Effect Plots with implicit Interaction Detection.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Explaining Hyperparameter Optimization via Partial Dependence Plots.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Pitfalls to Avoid when Interpreting Machine Learning Models.
CoRR, 2020

General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models.
Proceedings of the xxAI - Beyond Explainable AI, 2020


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