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Influence of the buoyancy on a jet in crossflow., , , and . J. Vis., 10 (3): 251 (2007)Towards deep learning-powered IVF: A large public benchmark for morphokinetic parameter prediction., , , , , , and . CoRR, (2022)Dynamical Algebraic Combinatorics, Asynchronous Cellular Automata, and Toggling Independent Sets., , , , and . AUTOMATA, volume 90 of OASIcs, page 5:1-5:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2021)Inferring Boolean Networks from Single-Cell Human Embryo Datasets., , , and . ISBRA, volume 14248 of Lecture Notes in Computer Science, page 431-441. Springer, (2023)Targeted domain assembly for fast functional profiling of metagenomic datasets with S3A., , , and . Bioinform., 36 (13): 3975-3981 (2020)Vortex shedding process investigation downstream a surface-mounted block., , and . J. Vis., 8 (2): 99-108 (2005)Development of deep-learning approaches to discover metabolic interaction networks of environmental microbial communities from large metagenomic datasets, domain co-occurrence and protein coevolution. (Développement d'approches d'apprentissage profond pour découvrir les réseaux d'interactions métaboliques des communautés microbiennes environnementales à partir de vastes ensembles de données métagénomiques, co-occurrence de domaines et coévolution des protéines).. Sorbonne University, Paris, France, (2021)Meet-U: Educating through research immersion., , , , , , , , , and 39 other author(s). PLoS Comput. Biol., (2018)Chitosan solutions as injectable systems for dermal filler applications: Rheological characterization and biological evidence., , , , , , and . EMBC, page 2596-2599. IEEE, (2015)Static Determination of Probabilistic Execution Times., and . ECRTS, page 223-230. IEEE Computer Society, (2004)