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learning algorithm that leverages information contained in low-amplitude gravity perturbations (coined PEGS for Prompt Elasto-Gravity Signals, Vallée et al., 2017) to provide rapid unsaturated magnitude
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structured data processing and an opening toward applications in software engineering. Research program The project will investigate how to generate and execute specialized LLM-based workflows from high-level
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Cardioembolic Stroke Risk Stratification using AI Accelerated Patient-Specific Blood Flow Simulation
the left atrial appendage. Second, CFD simulates high-resolution hemodynamics but requires patient-specific geometry, wall mechanics, and boundary conditions, as well as demanding advanced imaging and
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Context Recent advances in computer vision and generative AI have enabled major breakthroughs in image and video understanding. However, modern deep learning models remain critically dependent
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group: MARIANNE (https://team.inria.fr/marianne/). The MARIANNE project-team pursues high-impact research in Artificial Intelligence with a focus on data and models for computational argumentation in
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. Pfeifer, W. Maass, Towards a theoretical foundation for morphological computation with compliant bodies. Biol. Cybern. 105, 355-370 (2011). • E. Lauga, T. R. Powers, The hydrodynamics of swimming