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of PEGS, the point-source approximation will not hold to model GNSS co-seismic signals. Therefore, we will generate an exhaustive set of realistic co-seismic slip distributions to compute synthetic GNSS
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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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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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. 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