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Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon

Learning domain invariant representations by joint Wasserstein distance minimization.

July 31 , 2023
https://doi.org/10.1016/j.neunet.2023.07.028

Yancan Mao, Jianjun Zhao, Zhonghao Yang, Shuhao Zhang, Haikun Liu, Volker Markl

MorphStream: Scalable Processing of Transactions over Streams on Multicores

July 24 , 2023
https://doi.org/10.48550/arXiv.2307.12749

Armin W. Thomas, Ulman Lindenberger, Wojciech Samek, Klaus-Robert Müller

Evaluating deep transfer learning for whole-brain cognitive decoding.

July 13 , 2023
https://doi.org/10.1016/j.jfranklin.2023.07.015

Lukas Muttenthaler, Robert A. Vandermeulen, Qiuyi Zhang, Thomas Unterthiner, Klaus-Robert Müller

Set Learning for Accurate and Calibrated Models

July 10 , 2023
https://arxiv.org/pdf/2307.02245.pdf

Joshua Scheidt, Alexander Diener, Michael Maiworm, Klaus-Robert Müller, Rolf Findeisen, Kurt Driessens, F. Stefan Tautz, Christian Wagner

Concept for the Real-Time Monitoring of Molecular Configurations during Manipulation with a Scanning Probe Microscope.

July 10 , 2023
https://doi.org/10.1021/acs.jpcc.3c02072

Kirill Bykov, Mayukh Deb, Dennis Grinwald, Klaus-Robert Müller, Marina M.-C. Höhne

DORA: Exploring Outlier Representations in Deep Neural Networks

July 10 , 2023
https://doi.org/10.48550/arXiv.2206.04530

Anh Duc Vu, Christos Tsigkanos, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Timo Kehrer

On Irregularity Localization for Scientific Data Analysis Workflows

July 03 , 2023
https://doi.org/10.1007/978-3-031-35995-8_24

Yordan Grigorov, Haralampos Gavriilidis, Sergey Redyuk, Kaustubh Beedkar, Volker Markl

P2D: A Transpiler Framework for Optimizing Data Science Pipelines

June 18 , 2023
https://dl.acm.org/doi/abs/10.1145/3595360.3595853