Lukas Schott

According to our database, Lukas Schott authored at least 13 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Challenging Common Assumptions in Multi-task Learning.

Cathrin Elich, Lukas Kirchdorfer, Jan M. Köhler, Lukas Schott

CoRR, 2023

Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles.

Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin Adric Dunn

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Visual Representation Learning Does Not Generalize Strongly Within the Same Domain.

Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Selected Inductive Biases in Neural Networks To Generalize Beyond the Training Domain.

Lukas Schott

PhD thesis, 2021

Score-Based Generative Classifiers.

Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt

CoRR, 2021

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding.

David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

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

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

CoRR, 2020

A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions.

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

Proceedings of the Computer Vision - ECCV 2020, 2020

2019

Towards the first adversarially robust neural network model on MNIST.

Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Robust Perception through Analysis by Synthesis.

Lukas Schott, Jonas Rauber, Wieland Brendel, Matthias Bethge

CoRR, 2018

2017

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

Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht

Proceedings of the IEEE International Conference on Computer Vision, 2017

Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction.

Shengdong Zhang, Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

2015

Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning.

Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah

CoRR, 2015