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DTSTART;TZID=Europe/Paris:20250703T153000
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DTSTAMP:20260502T003756
CREATED:20250630T095224Z
LAST-MODIFIED:20250717T073820Z
UID:7156-1751556600-1751556600@isdm.umontpellier.fr
SUMMARY:Machine Learning in Montpellier\, Theory & Practice
DESCRIPTION:Simulating Environment-Conditioned Seabird Trajectories with Generative AI \nCampus St Priest (860 Rue Saint Priest 34095 Montpellier Cedex 5)\, bat. 5\, Room: 02.124\nMachine Learning in Montpellier\, Theory & Practice – Pedro Valdeira \nJulien Patras (IRD / Marbec) will give a talk : Seabirds serve as key bioindicators of ocean health\, and with modern tracking technologies like GPS tags\, we now have rich datasets capturing their offshore movements. These trajectory data enable us to study behavioral states and identify ecologically significant foraging zones. However\, modeling how environmental variables (like wind\, sea surface temperature\, or currents) shape these trajectories remains largely unexplored. Trajectory simulation using generative artificial intelligence has shown great promise in fields like autonomous driving and human motion modeling. Inspired by these advances\, we introduce a novel approach in movement ecology by adapting DiffTraj (Zhu et al.\, 2023)\,a pretrained diffusion model originally developed for vehicle trajectories. We then adapt and fine-tune the model on seabird movement data\, so that it supports multi-species\, multi-site simulation\, with the aim of environmental conditioned generation\, and improving state-of-the-art seabird trajectory simulation. \nVisio\nEn savoir plus
URL:https://isdm.umontpellier.fr/event/simulating-environment-conditioned-seabird-trajectories-with-generative-ai/
CATEGORIES:Séminaire
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