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X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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DTSTART:20250330T010000
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DTSTART;TZID=Europe/Paris:20250403T140000
DTEND;TZID=Europe/Paris:20250403T150000
DTSTAMP:20260419T123100
CREATED:20250306T091427Z
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UID:11808-1743688800-1743692400@www.greyc.fr
SUMMARY:Séminaire Image : "Decomposable Symbolic Regression Using Transformers and Neural Network-Assisted Genetic Algorithms"\,  Giorgio Morales
DESCRIPTION:Nous aurons le plaisir d’écouter Giorgio Morales\, post-doc de l’équipe Image.\nIl donnera un séminaire IMAGE le jeudi 3 avril 2025 à 14h en salle de séminaire F-200. \nTitre : « Decomposable Symbolic Regression Using Transformers and Neural Network-Assisted Genetic Algorithms » \nRésumé :\nOne of the goals of science is to discover laws that serve as causal explanations for the observable world. Such discoveries may stem from distilling experimental data into analytical equations that allow interpretation of their underlying natural laws. This process is known as equation learning or symbolic regression (SR). Nevertheless\, most SR methods prioritize minimizing prediction error over identifying the governing equations\, often producing overly complex or inaccurate expressions. To address this\, in this talk\, I present a decomposable SR method that generates interpretable multivariate expressions leveraging transformer models\, genetic algorithms (GAs)\, and genetic programming (GP). It first generates multiple univariate skeletons that capture the functional relationship between each variable and the system’s response. These skeletons are systematically merged using evolutionary approaches\, ensuring interpretability throughout the process. The method was evaluated on problems with controlled and varying degrees of noise\, demonstrating lower or comparable interpolation and extrapolation errors compared to two GP-based and two neural SR methods. Unlike these methods\, this approach consistently learned expressions that matched the original mathematical structure.
URL:https://www.greyc.fr/event/seminaire-image-decomposable-symbolic-regression-using-transformers-and-neural-network-assisted-genetic-algorithms-giorgio-morales/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:Image,Seminaire Image
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