Berkant Turan

I am working on improving the interpretability of AI, focusing on the Merlin-Arthur Classifier. This intriguing model uses two feature selectors to generate meaningful saliency maps. My objectives are to fine-tune its architecture, explore its adversarial components, and evaluate its effectiveness with complex datasets.

📬 Contact

office
Room 3024 at ZIB
e-mail
homepage
b-turan.github.io
languages
German, English, and Turkish

🎓 Curriculum vitae

since 2022
Researcher at ZIB
2022 to 2022
Research Assistant at ZIB
Jan 2022
M.Sc. in Scientific Computing at TUB
Oct 2018
B.Sc. in Engineering Science at TUB

📝 Publications and preprints

Conference proceedings

  1. Wäldchen, S., Sharma, K., Turan, B., Zimmer, M., and Pokutta, S. (2024). Interpretability Guarantees with Merlin-Arthur Classifiers. Proceedings of International Conference on Artificial Intelligence and Statistics. [arXiv]
    [BibTeX]
    @inproceedings{wszp_merlinarthur_22,
      year = {2024},
      booktitle = {Proceedings of International Conference on Artificial Intelligence and Statistics},
      archiveprefix = {arXiv},
      eprint = {2206.00759},
      primaryclass = {cs.LG},
      author = {Wäldchen, Stephan and Sharma, Kartikey and Turan, Berkant and Zimmer, Max and Pokutta, Sebastian},
      title = {Interpretability Guarantees with Merlin-Arthur Classifiers}
    }

🔬 Projects

Expanding Merlin-Arthur Classifiers: Interpretable Neural Networks Through Interactive Proof Systems

Existing approaches for interpreting Neural Network classifiers that highlight features relevant for a decision are based solely on heuristics. We introduce a theory that allows us to bound the quality of the features without assumptions on the classifier model by relating classification to Interactive Proof Systems.

MATH+ EF1-24
Apr 2023 to Mar 2026
4
2

💬 Talks and posters

Conference and workshop talks

Sep 2023
Practical Insight Into Deep Learning Optimization
TES Summer School on Optimization and Machine Learning [PDF]
Jul 2023
Extending Merlin-Arthur Classifiers for Improved Interpretability
The 1st World Conference on EXplainable Artificial Intelligence

👨‍🏫Teaching

winter 2019
Tutor for Statics and Elementary Strength of Materials at TUB
summer 2018
Tutor for Energy-Based Methods in Mechanics at TUB
summer 2018
Tutor for Continuum Mechanics at TUB
winter 2018
Tutor for Kinematics and Dynamics at TUB
summer 2017
Tutor for Statics and Elementary Strength of Materials at TUB
winter 2017
Tutor for Energy-Based Methods in Mechanics at TUB
winter 2017
Tutor for Continuum Mechanics at TUB
summer 2016
Tutor for Kinematics and Dynamics at TUB
summer 2015
Tutor for Statics and Elementary Strength of Materials at TUB