Publications

Jules Scholler, Joel Jonsson, Tomás Jordá-Siquier, Ivana Gantar, Laura Batti, Bevan L Cheeseman, Stéphane Pagès, Ivo F Sbalzarini, and Christophe M Lamy. Efficient image analysis for large-scale next generation histopathology using pAPRica. bioRxiv, January 2023. [PUMA: Efficient analysis generation histopathology image large-scale {pAPRica} yaff]

Tieu-Long Phan, Klaus Weinbauer, Marcos E. Gonzalez Laffitte, Yingjie Pan, Daniel Merkle, Jakob L. Andersen, Rolf Fagerberg, Christoph Flamm, and Peter F. Stadler. SynTemp: Efficient Extraction of Graph-Based Reaction Rules from Large-Scale Reaction Databases. Journal of Chemical Information and Modeling, (65)6:2882-2896, American Chemical Society (ACS), September 2025. [PUMA: Databases Efficient Extraction Graph-Based Large-Scale Reaction Rules SynTemp xack yaff] URL

Anika Hannemann, Arjhun Swaminathan, Ali Burak Ünal, and Mete Akgün. Private, Efficient and Scalable Kernel Learning for Medical Image Analysis. 19th International Meeting, CIBB 2024, Benevento, Italy, September 4–6, 2024, Revised Selected Papers, 2025. [PUMA: Efficient Kernel_Learning Medical_Image_Analysis Private Scalable nopdf] URL

Nikolaus Hautsch, Ostap Okhrin, and Alexander Ristig. Maximum-Likelihood Estimation Using the Zig-Zag Algorithm. Journal of Financial Econometrics, (21)4:1346-1375, 2023. [PUMA: Bitcoin Gauß–Seidel conditional correlation dynamic efficient estimation iterative topic_engineering zno] URL

Chen Liu, Guillaume Bellec, Bernhard Vogginger, David Kappel, Johannes Partzsch, Felix Neumärker, Sebastian Höppner, Wolfgang Maass, Steve B Furber, Robert Legenstein, and 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 zno]