Publications

Niklas Deckers, und Martin Potthast. WARC-DL: Scalable Web Archive Processing for Deep Learning. 2022. [PUMA: Archive Deep Learning Processing Scalable WARC-DL Web Xack] URL

Dianzhao Li, und Ostap Okhrin. A platform-agnostic deep reinforcement learning framework for effective Sim2Real transfer towards autonomous driving. Commun Eng, (3)1:147, Springer Science and Business Media LLC, Oktober 2024. [PUMA: Sim2Real Xack autonomous deep driving framework learning platform-agnostic reinforcement]

Maksim Kukushkin, Martin Bogdan, und Thomas Schmid. On optimizing morphological neural networks for hyperspectral image classification. In Wolfgang Osten (Hrsg.), Sixteenth International Conference on Machine Vision (ICMV 2023), (13072):1307202, SPIE, 2024. [PUMA: classification computer deep hyperspectral image learning mathematical morphological morphology networks neuronal nopdf remote sensing vision] URL

Anderson P. Avila Santos, Breno L. S. de Almeida, Robson P. Bonidia, Peter F. Stadler, Polonca Stefanic, Ines Mandic-Mulec, Ulisses Rocha, Danilo S. Sanches, und André C.P.L.F. de Carvalho. BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification. RNA Biology, (21)1:410–421, Informa UK Limited, März 2024. [PUMA: BioDeepfuse RNA Zno classification deep extraction feature learning non-coding] URL

Jordan Richards, Raphaël Huser, Emanuele Bevacqua, und Jakob Zscheischler. Insights into the Drivers and Spatiotemporal Trends of Extreme Mediterranean Wildfires with Statistical Deep Learning. Artificial Intelligence for the Earth Systems, (2)4American Meteorological Society, Oktober 2023. [PUMA: Deep Extreme Learning Mediterranean Spatiotemporal Statistical Trends Wildfires zno] URL

Ravi Pradip, und Frank Cichos. Deep reinforcement learning with artificial microswimmers. Emerging Topics in Artificial Intelligence (ETAI) 2022, (12204):104--110, 2022. [PUMA: Deep artificial learning microswimmers nopdf reinforcement topic_physchemistry]

Martin Waltz, Ostap Okhrin, und Michael Schultz. Self-organized free-flight arrival for urban air mobility. Transportation Research Part C: Emerging Technologies, (167):104806, 2024. [PUMA: Deep Urban air eVTOL learning mobility reinforcement topic_engineering yaff] URL

Vincent D. Friedrich, Peter Pennitz, Emanuel Wyler, Julia M. Adler, Dylan Postmus, Kristina Müller, Luiz Gustavo Teixeira Alves, Julia Prigann, Fabian Pott, Daria Vladimirova, Thomas Hoefler, Cengiz Goekeri, Markus Landthaler, Christine Goffinet, Antoine-Emmanuel Saliba, Markus Scholz, Martin Witzenrath, Jakob Trimpert, Holger Kirsten, und Geraldine Nouailles. Neural network-assisted humanisation of COVID-19 hamster transcriptomic data reveals matching severity states in human disease. eBioMedicine, (108):105312, 2024. [PUMA: COVID-19, Cross-species Deep Disease Hamster RNA-seq, Single-cell analysis, learning matching, model, state topic_mathfoundation xack yaff] URL

Qinghe Zeng, Christophe Klein, Stefano Caruso, Pascale Maille, Narmin Ghaffari Laleh, Daniele Sommacale, Alexis Laurent, Giuliana Amaddeo, David Gentien, Audrey Rapinat, Hélène Regnault, Cécile Charpy, Cong Trung Nguyen, Christophe Tournigand, Raffaele Brustia, Jean Michel Pawlotsky, Jakob Nikolas Kather, Maria Chiara Maiuri, Nicolas Loménie, und Julien Calderaro. Artificial intelligence predicts immune and inflammatory gene signatures directly from hepatocellular carcinoma histology. J. Hepatol., (77)1:116--127, Elsevier BV, Juli 2022. [PUMA: topic_lifescience artificial deep gene image immune intelligence; learning; pathology; signatures; slide whole]

Alexander Kurz, Katja Hauser, Hendrik Alexander Mehrtens, Eva Krieghoff-Henning, Achim Hekler, Jakob Nikolas Kather, Stefan Fröhling, Christof von Kalle, und Titus Josef Brinker. Uncertainty estimation in medical image classification: Systematic review. JMIR Med. Inform., (10)8:e36427, August 2022. [PUMA: topic_lifescience calibration; classification; deep detection; estimation image imaging; learning; medical network out-of-distribution uncertainty]

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, und Jakob Nikolas Kather. Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology. Med. Image Anal., (79)102474:102474, Elsevier BV, Juli 2022. [PUMA: topic_lifescience Artificial Computational Convolutional Learning; Multiple-Instance Vision Weakly-supervised deep intelligence; learning networks; neural pathology; transformers;]

Peter Leonard Schrammen, Narmin Ghaffari Laleh, Amelie Echle, Daniel Truhn, Volkmar Schulz, Titus J Brinker, Hermann Brenner, Jenny Chang-Claude, Elizabeth Alwers, Alexander Brobeil, Matthias Kloor, Lara R Heij, Dirk Jäger, Christian Trautwein, Heike I Grabsch, Philip Quirke, Nicholas P West, Michael Hoffmeister, und Jakob Nikolas Kather. Weakly supervised annotation-free cancer detection and prediction of genotype in routine histopathology. J. Pathol., (256)1:50--60, Wiley, Januar 2022. [PUMA: topic_lifescience Lynch artificial cancer; colorectal computational deep digital instability intelligence; learning; microsatellite pathology; syndrome;]

Scarlet Brockmoeller, Amelie Echle, Narmin Ghaffari Laleh, Susanne Eiholm, Marie Louise Malmstrøm, Tine Plato Kuhlmann, Katarina Levic, Heike Irmgard Grabsch, Nicholas P West, Oliver Lester Saldanha, Katerina Kouvidi, Aurora Bono, Lara R Heij, Titus J Brinker, Ismayil Gögenür, Philip Quirke, und Jakob Nikolas Kather. Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer. J. Pathol., (256)3:269--281, Wiley, März 2022. [PUMA: topic_lifescience AI; LNM adipose and artificial biomarker; bowel cancer; colorectal deep digital early inflamed intelligence; learning; metastasis; new pT1 pT2 pathology; prediction predictive tissue;]

Roman C Maron, Achim Hekler, Sarah Haggenmüller, Christof von Kalle, Jochen S Utikal, Verena Müller, Maria Gaiser, Friedegund Meier, Sarah Hobelsberger, Frank F Gellrich, Mildred Sergon, Axel Hauschild, Lars E French, Lucie Heinzerling, Justin G Schlager, Kamran Ghoreschi, Max Schlaak, Franz J Hilke, Gabriela Poch, Sören Korsing, Carola Berking, Markus V Heppt, Michael Erdmann, Sebastian Haferkamp, Dirk Schadendorf, Wiebke Sondermann, Matthias Goebeler, Bastian Schilling, Jakob N Kather, Stefan Fröhling, Daniel B Lipka, Eva Krieghoff-Henning, und Titus J Brinker. Model soups improve performance of dermoscopic skin cancer classifiers. Eur. J. Cancer, (173):307--316, Elsevier BV, September 2022. [PUMA: topic_lifescience Artificial Calibration; Deep Dermatology; Ensembles; Generalisation; Melanoma; Model Nevus; Robustness intelligence; learning; soups;]

Chiara Maria Lavinia Loeffler, Nadina Ortiz Bruechle, Max Jung, Lancelot Seillier, Michael Rose, Narmin Ghaffari Laleh, Ruth Knuechel, Titus J Brinker, Christian Trautwein, Nadine T Gaisa, und Jakob N Kather. Artificial intelligence-based detection of FGFR3 mutational status directly from routine histology in bladder cancer: A possible preselection for molecular testing?. Eur. Urol. Focus, (8)2:472--479, Elsevier BV, März 2022. [PUMA: topic_lifescience Artificial Bladder Deep FGFR3 Molecular cancer; factor fibroblast for growth intelligence; learning; mutations; receptor testing therapy]

David Nam, Julius Chapiro, Valerie Paradis, Tobias Paul Seraphin, und Jakob Nikolas Kather. Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction. JHEP Rep., (4)4:100443, Elsevier BV, April 2022. [PUMA: topic_lifescience AI, Artificial CNN, Communications DICOM, Diagnosis; Digital HCC, Imaging Individual ML, MVI, Medicine; NAFLD, NASH, Prognosis Reporting TACE, TRIPOD, Transparent WSIs, a and artificial carcinoma; chemoembolisation; convolutional data deep diagnostic disease; fatty for hepatocellular images; imaging; in integration intelligence; invasion; learning; liver machine microvascular model multimodal multivariable network; neural non-alcoholic of or prediction slide steatohepatitis; support system; transarterial whole]

Benjamin P Brown, Oanh Vu, Alexander R Geanes, Sandeepkumar Kothiwale, Mariusz Butkiewicz, Edward W Lowe, Jr, Ralf Mueller, Richard Pape, Jeffrey Mendenhall, und Jens Meiler. Introduction to the BioChemical Library (BCL): An application-based open-source toolkit for integrated cheminformatics and machine learning in computer-aided drug discovery. Front. Pharmacol., (13):833099, Frontiers Media SA, Februar 2022. [PUMA: topic_lifescience BCL; QSAR; biochemical cheminformatics; deep design; discovery; drug library; network; neural open-source]

Lorenzo Maiello, Lorenzo Ball, Marco Micali, Francesca Iannuzzi, Nico Scherf, Ralf-Thorsten Hoffmann, Marcelo Gama de Abreu, Paolo Pelosi, und Robert Huhle. Automatic lung segmentation and quantification of aeration in computed tomography of the chest using 3D transfer learning. Front. Physiol., (12):725865, 2021. [PUMA: ARDS; COVID-19; Jaccard deep index; learning; lung recruitment; segmentation; transfer uNet]

Chen Liu, Guillaume Bellec, Bernhard Vogginger, David Kappel, Johannes Partzsch, Felix Neumärker, Sebastian Höppner, Wolfgang Maass, Steve B Furber, Robert Legenstein, und Christian G Mayr. Memory-efficient deep learning on a SpiNNaker 2 prototype. Front. Neurosci., (12):840, Frontiers Media SA, November 2018. [PUMA: SpiNNaker; deep efficient energy footprint; hardware; memory parallelism; pruning; rewiring; sparsity]

Ali Al-Fatlawi, Negin Malekian, Sebastián Garc\'ıa, Andreas Henschel, Ilwook Kim, Andreas Dahl, Beatrix Jahnke, Peter Bailey, Sarah Naomi Bolz, Anna R Poetsch, Sandra Mahler, Robert Grützmann, Christian Pilarsky, und Michael Schroeder. Deep learning improves pancreatic cancer diagnosis using RNA-based variants. Cancers (Basel), (13)11:2654, MDPI AG, Mai 2021. [PUMA: association cancer; chronic deep learning; pancreatic pancreatitis; study topic_lifescience transcriptome-wide]