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Disentanglement and Generalization Under Correlation Shifts


Dec 29, 2021
Christina M. Funke, Paul Vicol, Kuan-Chieh Wang, Matthias K├╝mmerer, Richard Zemel, Matthias Bethge


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Unsupervised Object Learning via Common Fate


Oct 13, 2021
Matthias Tangemann, Steffen Schneider, Julius von K├╝gelgen, Francesco Locatello, Peter Gehler, Thomas Brox, Matthias K├╝mmerer, Matthias Bethge, Bernhard Sch├Âlkopf


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Visual Representation Learning Does Not Generalize Strongly Within the Same Domain


Jul 23, 2021
Lukas Schott, Julius von K├╝gelgen, Frederik Tr├Ąuble, Peter Gehler, Chris Russell, Matthias Bethge, Bernhard Sch├Âlkopf, Francesco Locatello, Wieland Brendel


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How Well do Feature Visualizations Support Causal Understanding of CNN Activations?


Jun 23, 2021
Roland S. Zimmermann, Judy Borowski, Robert Geirhos, Matthias Bethge, Thomas S. A. Wallis, Wieland Brendel

* ICML 2021 XAI workshop version. Joint first and last authors. Project website at https://brendel-group.github.io/causal-understanding-via-visualizations/ 

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Partial success in closing the gap between human and machine vision


Jun 14, 2021
Robert Geirhos, Kantharaju Narayanappa, Benjamin Mitzkus, Tizian Thieringer, Matthias Bethge, Felix A. Wichmann, Wieland Brendel

* A preliminary version of this work was presented as Oral at the 2020 NeurIPS workshop on "Shared Visual Representations in Human & Machine Intelligence" (arXiv:2010.08377) 

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Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling


May 27, 2021
Akis Linardos, Matthias K├╝mmerer, Ori Press, Matthias Bethge

* Joint first authors 

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Adapting ImageNet-scale models to complex distribution shifts with self-learning


Apr 28, 2021
Evgenia Rusak, Steffen Schneider, Peter Gehler, Oliver Bringmann, Wieland Brendel, Matthias Bethge

* Web: https://domainadaptation.org/selflearning 

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State-of-the-Art in Human Scanpath Prediction


Feb 24, 2021
Matthias K├╝mmerer, Matthias Bethge


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