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, such as Bayesian approaches and fossilized birth–death models, to reconstruct robust phylogenies and estimate divergence times. It also investigates macroevolutionary dynamics, including variation in
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territories. The pedigrees reconstructed in each populations are sufficient to estimate some simple quantitative genetic parameters, but they are incomplete and contain errors, which greatly limits
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there are innumerable examples of its application, one important observation is the low proportion of studies proposing the estimation of uncertainties (<5%). Yet uncertainties can be multiple and of different natures
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 3 days ago
specifically, we use simulation-based inference (SBI) [1], a Bayesian approach that leverages deep generative models, such as conditional normalizing flows and score-diffusion models, to approximate
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, so that it can be easily used in practice (fast optimization, embedded decision-making, online updating). 1. Design a lightweight statistical/probabilistic surrogate model, integrating: • an estimation
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, clustering analyses, propagating location and other uncertainties...) of mid-ocean ridge catalogs, using standard, Bayesian and machine learning techniques. ⁃ Implement methodologies that improve estimates
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non stationnaires. Dans ces représentations (STFT/ spectro- gramme, ondelettes, etc.), les composantes d'intérêt apparaissent sous forme de ridges. Estimer ces ridges suffit alors à reconstruire les
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 8 days ago
are available, from computer graphics, computer engineering, computational physics, biology and chemistry, and so on. When training data is produced from simulation codes, it can be generated along with
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associated with phenotypic (biomechanical and metabolomics) traits. Estimate locus-specific effect sizes and quantifying genetically-driven phenotypic variations. Develop Bayesian models and/or deep learning
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features to behavior using GLMMs/Bayesian models; conduct sensitivity and robustness checks. * Method validation: benchmark alternative pipelines (filters, burst detectors, forward/inverse models); perform