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Is Deep Image Prior in Need of a Good Education?


Nov 23, 2021
Riccardo Barbano, Johannes Leuschner, Maximilian Schmidt, Alexander Denker, Andreas Hauptmann, Peter Maaß, Bangti Jin


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Conditional Invertible Neural Networks for Medical Imaging


Oct 26, 2021
Alexander Denker, Maximilian Schmidt, Johannes Leuschner, Peter Maass


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Evolving Neuronal Plasticity Rules using Cartesian Genetic Programming


Feb 08, 2021
Henrik D. Mettler, Maximilian Schmidt, Walter Senn, Mihai A. Petrovici, Jakob Jordan

* 2 pages, 1 figure 

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ADVISER: A Toolkit for Developing Multi-modal, Multi-domain and Socially-engaged Conversational Agents


May 04, 2020
Chia-Yu Li, Daniel Ortega, Dirk Väth, Florian Lux, Lindsey Vanderlyn, Maximilian Schmidt, Michael Neumann, Moritz Völkel, Pavel Denisov, Sabrina Jenne, Zorica Kacarevic, Ngoc Thang Vu

* All authors contributed equally. Accepted to be presented at ACL - System demonstrations - 2020 

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Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods


Mar 12, 2020
Daniel Otero Baguer, Johannes Leuschner, Maximilian Schmidt


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Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data


Dec 10, 2019
Christian Etmann, Maximilian Schmidt, Jens Behrmann, Tobias Boskamp, Lena Hauberg-Lotte, Annette Peter, Rita Casadonte, Jörg Kriegsmann, Peter Maass


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The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods


Oct 01, 2019
Johannes Leuschner, Maximilian Schmidt, Daniel Otero Baguer, Peter Maaß


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Normalizing flows for novelty detection in industrial time series data


Jun 17, 2019
Maximilian Schmidt, Marko Simic

* Presented at "First workshop on Invertible Neural Networks and Normalizing Flows(ICML 2019), Long Beach, CA, USA" 

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