Publications

Peter Winkler, Norman Koch, Andreas Hornig, and Johannes Gerritzen. OmniOpt – A tool for hyperparameter optimization on HPC. In Heike Jagode, Hartwig Anzt, Hatem Ltaief, and Piotr Luszczek (Eds.), High Performance Computing - ISC High Performance Digital 2021 International Workshops, 2021, Revised Selected Papers, 285--296, Springer, Berlin u. a., Germany, Nov 13, 2021. [PUMA: FIS_scads High Hyperparameter Neural computing, networks optimization, performance]

Nishant Kumar, Lukas Krause, Thomas Wondrak, Sven Eckert, Kerstin Eckert, and Stefan Gumhold. Robust Reconstruction of the Void Fraction from Noisy Magnetic Flux Density Using Invertible Neural Networks. Sensors, (24)42024. [PUMA: topic_visualcomputing Density Flux Fraction Invertible Magnetic Networks Neural Noisy Reconstruction Void] URL

Timo P. Gros, David Groß, Stefan Gumhold, Jörg Hoffmann, Michaela Klauck, and Marcel Steinmetz. TraceVis: Towards Visualization for Deep Statistical Model Checking. Leveraging Applications of Formal Methods, Verification and Validation: Tools and Trends: 9th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2020, Rhodes, Greece, October 20–30, 2020, Proceedings, Part IV, 27–46, Springer-Verlag, Berlin, Heidelberg, 2020. [PUMA: Checking Model Networks Neural Statistical Visualization] URL

Lucas Schneider, Sara Laiouar-Pedari, Sara Kuntz, Eva Krieghoff-Henning, Achim Hekler, Jakob N Kather, Timo Gaiser, Stefan Fröhling, and Titus J Brinker. Integration of deep learning-based image analysis and genomic data in cancer pathology: A systematic review. Eur. J. Cancer, (160):80--91, Elsevier BV, January 2022. [PUMA: topic_lifescience Biomarker Cancer; Convolutional Multimodal Omics fusion; identification; networks; neural]

Narmin Ghaffari Laleh, Hannah Sophie Muti, Chiara Maria Lavinia Loeffler, Amelie Echle, Oliver Lester Saldanha, Faisal Mahmood, Ming Y Lu, Christian Trautwein, Rupert Langer, Bastian Dislich, Roman D Buelow, Heike Irmgard Grabsch, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Titus J Brinker, Firas Khader, Daniel Truhn, Nadine T Gaisa, Peter Boor, Michael Hoffmeister, Volkmar Schulz, and Jakob Nikolas Kather. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, July 2022. [PUMA: topic_lifescience Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]