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Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding

Jul 21, 2020
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan Paiton

* Code is available at https://github.com/bethgelab/slow_disentanglement. The first three authors, as well as the last two authors, contributed equally 

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Increasing the robustness of DNNs against image corruptions by playing the Game of Noise

Feb 26, 2020
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel


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Towards the first adversarially robust neural network model on MNIST

Sep 20, 2018
Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel


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Learned Watershed: End-to-End Learning of Seeded Segmentation

Sep 04, 2017
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred Hamprecht

* The first two authors contributed equally 

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Comparative Study of Deep Learning Software Frameworks

Mar 30, 2016
Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

* Submitted to KDD 2016 with TensorFlow results added. At the time of submission to KDD, TensorFlow was available only with cuDNN v.2 and thus its performance is reported with that version 

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