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Patrick Schramowski
Patrick Schramowski
Verified email at cs.tu-darmstadt.de
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Year
Making deep neural networks right for the right scientific reasons by interacting with their explanations
P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ...
Nature Machine Intelligence 2 (8), 476-486, 2020
112*2020
Pad\'e Activation Units: End-to-end Learning of Flexible Activation Functions in Deep Networks
A Molina, P Schramowski, K Kersting
arXiv preprint arXiv:1907.06732, 2019
412019
Right for the right concept: Revising neuro-symbolic concepts by interacting with their explanations
W Stammer, P Schramowski, K Kersting
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
382021
The Moral Choice Machine: Semantics derived automatically from language corpora contain human-like moral choices
S Jentzsch, P Schramowski, C Rothkopf, K Kersting
Proceedings of the 2nd AAAI/ACM Conference on AI, Ethics, and Society. Palo …, 2019
37*2019
Laion-5b: An open large-scale dataset for training next generation image-text models
C Schuhmann, R Beaumont, R Vencu, C Gordon, R Wightman, M Cherti, ...
arXiv preprint arXiv:2210.08402, 2022
272022
Extending hyperspectral imaging for plant phenotyping to the UV-range
A Brugger, J Behmann, S Paulus, HG Luigs, MT Kuska, P Schramowski, ...
Remote Sensing 11 (12), 1401, 2019
272019
Large pre-trained language models contain human-like biases of what is right and wrong to do
P Schramowski, C Turan, N Andersen, CA Rothkopf, K Kersting
Nature Machine Intelligence 4 (3), 258-268, 2022
25*2022
The moral choice machine
P Schramowski, C Turan, S Jentzsch, C Rothkopf, K Kersting
Frontiers in artificial intelligence, 36, 2020
232020
Right for better reasons: Training differentiable models by constraining their influence functions
X Shao, A Skryagin, W Stammer, P Schramowski, K Kersting
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9533-9540, 2021
172021
BERT has a Moral Compass: Improvements of ethical and moral values of machines
P Schramowski, C Turan, S Jentzsch, C Rothkopf, K Kersting
arXiv preprint arXiv:1912.05238, 2019
172019
Spectral signatures in the UV range can be combined with secondary plant metabolites by deep learning to characterize barley–powdery mildew interaction
A Brugger, P Schramowski, S Paulus, U Steiner, K Kersting, AK Mahlein
Plant Pathology 70 (7), 1572-1582, 2021
72021
Neural conditional gradients
P Schramowski, C Bauckhage, K Kersting
arXiv preprint arXiv:1803.04300, 2018
52018
A Typology to Explore and Guide Explanatory Interactive Machine Learning
F Friedrich, W Stammer, P Schramowski, K Kersting
arXiv preprint arXiv:2203.03668, 2022
42022
Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?
P Schramowski, C Tauchmann, K Kersting
arXiv preprint arXiv:2202.06675, 2022
4*2022
Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations
W Stammer, M Memmel, P Schramowski, K Kersting
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
42022
Recurrent Rational Networks
Q Delfosse, P Schramowski, A Molina, K Kersting
arXiv preprint arXiv:2102.09407, 2021
32021
Interactively generating explanations for transformer language models
P Schramowski, F Friedrich, C Tauchmann, K Kersting
arXiv preprint arXiv:2110.02058, 2021
22021
Machine Learning Assisted Pattern Matching: Insight into Oxide Electronic Device Performance by Phase Determination in 4D-STEM Datasets
A Zintler, R Eilhardt, S Wang, M Krajnak, P Schramowski, W Stammer, ...
Microscopy and Microanalysis 26 (S2), 1908-1909, 2020
22020
Do Multilingual Language Models Capture Differing Moral Norms?
K Hämmerl, B Deiseroth, P Schramowski, J Libovický, A Fraser, ...
arXiv preprint arXiv:2203.09904, 2022
12022
Hyperspectral imaging in the UV-range allows for differentiation of sugar beet diseases based on changes of secondary plant metabolites
A Brugger, F Ispizua Yamati, A Barreto, S Paulus, P Schramowski, ...
Phytopathology, 2022
12022
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