Moritz Böhle (PhD Student)

“Good Teachers Explain: Explanation-Enhanced Knowledge Distillation,” in Computer Vision -- ECCV 2024, Milano, Italy.

@inproceedings{ParchamiAraghiECCV24,
TITLE = {Good Teachers Explain: Explanation-Enhanced Knowledge Distillation},
AUTHOR = {Parchami-Araghi, Amin and Boehle, Moritz Daniel and Rao, Sukrut Sridhar and Schiele, Bernt},
LANGUAGE = {eng},
PUBLISHER = {Springer},
YEAR = {2024},
PUBLREMARK = {Accepted},
BOOKTITLE = {Computer Vision -- ECCV 2024},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Milano, Italy},
}

%0 Conference Proceedings
%A Parchami-Araghi, Amin
%A Boehle, Moritz Daniel
%A Rao, Sukrut Sridhar
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Good Teachers Explain: Explanation-Enhanced Knowledge Distillation : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-5534-7
%D 2024
%B 18th European Conference on Computer Vision 
%Z date of event: 2024-09-29 - 2024-10-04
%C Milano, Italy
%B Computer Vision -- ECCV 2024 
%I Springer
%B Lecture Notes in Computer Science

“Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery,” in Computer Vision -- ECCV 2024, Milano, Italy.

@inproceedings{RaoECCV24,
TITLE = {Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery},
AUTHOR = {Rao, Sukrut Sridhar and Mahajan, Sweta and B{\"o}hle, Moritz and Schiele, Bernt},
LANGUAGE = {eng},
PUBLISHER = {Springer},
YEAR = {2024},
PUBLREMARK = {Accepted},
BOOKTITLE = {Computer Vision -- ECCV 2024},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Milano, Italy},
}

%0 Conference Proceedings
%A Rao, Sukrut Sridhar
%A Mahajan, Sweta
%A Böhle, Moritz
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Discover-then-Name: Task-Agnostic Concept Bottlenecks via Automated Concept Discovery : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-9A97-9
%D 2024
%B 18th European Conference on Computer Vision 
%Z date of event: 2024-09-29 - 2024-10-04
%C Milano, Italy
%B Computer Vision -- ECCV 2024
%I Springer
%B Lecture Notes in Computer Science

“Better Understanding Differences in Attribution Methods via Systematic Evaluations,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 46, no. 6, 2024.

@article{RaoTPAMI24,
TITLE = {Better Understanding Differences in Attribution Methods via Systematic Evaluations},
AUTHOR = {Rao, Sukrut and Boehle, Moritz and Schiele, Bernt},
LANGUAGE = {eng},
DOI = {10.1109/TPAMI.2024.3353528},
PUBLISHER = {IEEE},
ADDRESS = {Piscataway, NJ},
YEAR = {2024},
DATE = {2024},
JOURNAL = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
VOLUME = {46},
NUMBER = {6},
PAGES = {4090--4101},
}

%0 Journal Article
%A Rao, Sukrut
%A Boehle, Moritz
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Better Understanding Differences in Attribution Methods via Systematic Evaluations : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-5532-9
%R 10.1109/TPAMI.2024.3353528
%7 2024
%D 2024
%J IEEE Transactions on Pattern Analysis and Machine Intelligence
%V 46
%N 6
%& 4090
%P 4090 - 4101
%I IEEE
%C Piscataway, NJ

“Towards Designing Inherently Interpretable Deep Neural Networks for Image Classification,” Universität des Saarlandes, Saarbrücken, 2024.

@phdthesis{BoehlePhD24,
TITLE = {Towards Designing Inherently Interpretable Deep Neural Networks for Image Classification},
AUTHOR = {B{\"o}hle, Moritz},
LANGUAGE = {eng},
URL = {urn:nbn:de:bsz:291--ds-421904},
DOI = {10.22028/D291-42190},
SCHOOL = {Universit{\"a}t des Saarlandes},
ADDRESS = {Saarbr{\"u}cken},
YEAR = {2024},
DATE = {2024},
}

%0 Thesis
%A Böhle, Moritz
%Y Schiele, Bernt
%Y Fritz, Mario
%A referee: Akata, Zeynep
%A referee: Brendel, Wieland
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
International Max Planck Research School, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
External Organizations
External Organizations
%T Towards Designing Inherently Interpretable Deep Neural Networks for Image Classification : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000F-76AA-D
%U urn:nbn:de:bsz:291--ds-421904
%R 10.22028/D291-42190
%F OTHER: hdl:20.500.11880/37907
%I Universität des Saarlandes
%C Saarbrücken
%D 2024
%P XIII, 265 p.
%V phd
%9 phd
%U https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/37907

“Studying How to Efficiently and Effectively Guide Models with Explanations,” in IEEE/CVF International Conference on Computer Vision (ICCV 2023), Paris, France, 2023.

@inproceedings{Rao_ICCV23,
TITLE = {Studying How to Efficiently and Effectively Guide Models with Explanations},
AUTHOR = {Rao, Sukrut and B{\"o}hle, Moritz and Parchami-Araghi, Amin and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {979-8-3503-0718-4},
DOI = {10.1109/ICCV51070.2023.00184},
PUBLISHER = {IEEE},
YEAR = {2023},
MARGINALMARK = {$\bullet$},
DATE = {2023},
BOOKTITLE = {IEEE/CVF International Conference on Computer Vision (ICCV 2023)},
PAGES = {1922--1933},
ADDRESS = {Paris, France},
}

%0 Conference Proceedings
%A Rao, Sukrut
%A Böhle, Moritz
%A Parchami-Araghi, Amin
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Studying How to Efficiently and Effectively Guide Models with Explanations : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000D-CA7B-6
%R 10.1109/ICCV51070.2023.00184
%D 2023
%B IEEE/CVF International Conference on Computer Vision
%Z date of event: 2023-10-02 - 2023-10-06
%C Paris, France
%B IEEE/CVF International Conference on Computer Vision
%P 1922 - 1933
%I IEEE
%@ 979-8-3503-0718-4

“B-cos Networks: Alignment is All We Need for Interpretability,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 2022.

@inproceedings{Boehle_CVPR2022,
TITLE = {B-cos Networks: {A}lignment is All We Need for Interpretability},
AUTHOR = {B{\"o}hle, Moritz and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-6946-3},
DOI = {10.1109/CVPR52688.2022.01008},
PUBLISHER = {IEEE},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)},
PAGES = {10319--10328},
ADDRESS = {New Orleans, LA, USA},
}

%0 Conference Proceedings
%A Böhle, Moritz
%A Fritz, Mario
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T B-cos Networks: Alignment is All We Need for Interpretability : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000A-6F96-1
%R 10.1109/CVPR52688.2022.01008
%D 2022
%B 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition
%Z date of event: 2022-06-19 - 2022-06-24
%C New Orleans, LA, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 10319 - 10328
%I IEEE
%@ 978-1-6654-6946-3

“Towards Better Understanding Attribution Methods,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022), New Orleans, LA, USA, 2022.

@inproceedings{Rao_CVPR2022,
TITLE = {Towards Better Understanding Attribution Methods},
AUTHOR = {Rao, Sukrut and B{\"o}hle, Moritz and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-6946-3},
DOI = {10.1109/CVPR52688.2022.00998},
PUBLISHER = {IEEE},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2022)},
PAGES = {10213--10222},
ADDRESS = {New Orleans, LA, USA},
}

%0 Conference Proceedings
%A Rao, Sukrut
%A Böhle, Moritz
%A Schiele, Bernt
%+ Computer Graphics, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Towards Better Understanding Attribution Methods : 
%G eng
%U http://hdl.handle.net/21.11116/0000-000A-6F91-6
%R 10.1109/CVPR52688.2022.00998
%D 2022
%B 35th IEEE/CVF Conference on Computer Vision and Pattern Recognition
%Z date of event: 2022-06-19 - 2022-06-24
%C New Orleans, LA, USA
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 10213 - 10222
%I IEEE
%@ 978-1-6654-6946-3

“Optimising for Interpretability: Convolutional Dynamic Alignment Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 6, 2022.

@article{Boehle2109.13004,
TITLE = {Optimising for Interpretability: Convolutional Dynamic Alignment Networks},
AUTHOR = {B{\"o}hle, Moritz Daniel and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISSN = {0162-8828},
DOI = {10.1109/TPAMI.2022.3226041},
PUBLISHER = {IEEE},
ADDRESS = {Piscataway, NJ},
YEAR = {2022},
MARGINALMARK = {$\bullet$},
JOURNAL = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
VOLUME = {45},
NUMBER = {6},
PAGES = {7625--7638},
}

%0 Journal Article
%A Böhle, Moritz Daniel
%A Fritz, Mario
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Optimising for Interpretability: Convolutional Dynamic Alignment
  Networks : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0009-8113-F
%R 10.1109/TPAMI.2022.3226041
%7 2022
%D 2022
%J IEEE Transactions on Pattern Analysis and Machine Intelligence
%O IEEE Trans. Pattern Anal. Mach. Intell.
%V 45
%N 6
%& 7625
%P 7625 - 7638
%I IEEE
%C Piscataway, NJ
%@ false

“Convolutional Dynamic Alignment Networks for Interpretable Classifications,” in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, USA (Virtual), 2021.

@inproceedings{Boehle_CVPR21,
TITLE = {Convolutional Dynamic Alignment Networks for Interpretable Classifications},
AUTHOR = {B{\"o}hle, Moritz Daniel and Fritz, Mario and Schiele, Bernt},
LANGUAGE = {eng},
ISBN = {978-1-6654-4509-2},
DOI = {10.1109/CVPR46437.2021.00990},
PUBLISHER = {IEEE},
YEAR = {2021},
MARGINALMARK = {$\bullet$},
BOOKTITLE = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021)},
PAGES = {10029--10038},
ADDRESS = {Nashville, TN, USA (Virtual)},
}

%0 Conference Proceedings
%A Böhle, Moritz Daniel
%A Fritz, Mario
%A Schiele, Bernt
%+ Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
External Organizations
Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society
%T Convolutional Dynamic Alignment Networks for Interpretable Classifications : 
%G eng
%U http://hdl.handle.net/21.11116/0000-0008-1863-E
%R 10.1109/CVPR46437.2021.00990
%D 2021
%B 34th IEEE Conference on Computer Vision and Pattern Recognition
%Z date of event: 2021-06-19 - 2021-06-25
%C Nashville, TN, USA (Virtual)
%B IEEE/CVF Conference on Computer Vision and Pattern Recognition
%P 10029 - 10038
%I IEEE
%@ 978-1-6654-4509-2