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Leon Sixt
Leon Sixt
PhD Student, Frei Universität Berlin
Verified email at fu-berlin.de - Homepage
Title
Cited by
Cited by
Year
RenderGAN: Generating realistic labeled data
L Sixt, B Wild, T Landgraf
Frontiers in Robotics and AI 5, 66, 2018
1622018
Restricting the Flow: Information Bottlenecks for Attribution
K Schulz, L Sixt, F Tombari, T Landgraf
International Conference on Learning Representations, 2020
972020
When Explanations Lie: Why Many Modified BP Attributions Fail
L Sixt, M Granz, T Landgraf
International Conference on Machine Learning, 9046-9057, 2020
82*2020
Automatic localization and decoding of honeybee markers using deep convolutional neural networks
B Wild, L Sixt, T Landgraf
arXiv preprint arXiv:1802.04557, 2018
222018
Rendergan: Generating realistic labeled data–with an application on decoding bee tags
L Sixt
unpublished Bachelor Thesis, Freie Universität, Berlin, 2016
92016
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset
L Sixt, M Schuessler, OI Popescu, P Weiß, T Landgraf
arXiv preprint arXiv:2204.11642, 2022
22022
Two4two: Evaluating interpretable machine learning-a synthetic dataset for controlled experiments
M Schuessler, P Weiß, L Sixt
arXiv preprint arXiv:2105.02825, 2021
22021
Interpretability Through Invertibility: A Deep Convolutional Network With Ideal Counterfactuals And Isosurfaces
L Sixt, M Schuessler, P Weiß, T Landgraf
22020
DNNR: Differential Nearest Neighbors Regression
Y Nader, L Sixt, T Landgraf
arXiv preprint arXiv:2205.08434, 2022
2022
Analyzing a Caching Model
L Sixt, EZ Liu, M Pellat, J Wexler, H Milad, B Kim, M Maas
arXiv preprint arXiv:2112.06989, 2021
2021
The emojicite package Adds Emojis to Citations
L Sixt
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