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fait appel à des « pipelines » d'analyse qui associent les technologies de séquençage innovantes aux algorithmes bioinformatiques pour assembler, annoter et comparer les génomes viraux. Le projet
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Automated Generation of Digital Twins of Fractured Tibial Plateaus for Personalized Surgical plannin
currently relies solely on the surgeon’s expertise [2]. Unlike scheduled orthopedic procedures, trauma surgery has seen little integration of artificial intelligence in preoperative planning. Currently
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mesh complexity. Most greedy algorithms utilize local operators [2, 1], or variational approaches [5] or different stages (topology, then geometry) [6], or a larger repertoire of operators [9]. More
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differences or random direction stochastic approximations, offer general-purpose strategies that only rely on function evaluations. While conceptually simple, zeroth-order methods tend to scale poorly with
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suitable data models [CSC+23]. Objectives As far as the design of efficient numerical algorithms in an off-the-grid setting is concerned, the problem is challenging, since the optimization is defined in
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on their vulnerabilities against those attacks. While, the existing recent literature on the study of such attacks for FL mostly concentrates on deep learning. The PhD candidate will also investigate different ML algorithms
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survival of lung cancer patient, notably those targeting different driver mutations such as EGFR, ALK, KRAS, and ROS1. The treatments targeting KRAS G12C mutation, one of the most frequent genomic alteration
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of persistent AF. However, this therapy depends heavily on the practitioner’s subjectivity, with rather variable protocols and success rates reported by different centers. The development of robust, widely
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the technical side, we aim at combining statistical latent variable models with deep learning algorithms to justify existing results and allow a better understanding of their performances and their limitations