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Financement de l’UE (413 380 €) : Un réseau de neurones récurrents d’intégration probabiliste pour des applications scientifiques Hor02/05/2025 Programme de recherche et d'innovation de l'UE « Horizon »
Texte
Un réseau de neurones récurrents d’intégration probabiliste pour des applications scientifiques
Scientists have huge needs for better analysis tools. Machine learning is a powerful framework to provide outstanding tools, but the current large-scale neural networks are not adapted for scientific applications where datasets are limited. Probabilistic networks are a powerful alternative for smaller datasets. However, they have flaws that prevent them to work well for complex tasks. They notably have speed and accuracy limitations. This project aims to make a breakthrough in machine learning for scientific applications by developing a new physics-informed probabilistic neural network adapted for small datasets. The basic unit of our network overcomes the limitations of the current probabilistic methods by considering a recurrent Gaussian process and using an analytical integration method. The first objective of our project is to deploy several units that each represent a state in a neural network, and to consider abrupt transitions from one state to another. This network will be applied to the analysis of single-particle tracking data, an important and complex biology problem for which our model will be particularly well-suited. Next, we will extend our network to consider maps and spatiotemporal maps. This second phase will be applied to mapping cell viscosity, a particularly promising super-resolution technique that does not require specific markers. Our last objective is to create a modular network to enable better scalability of our architecture for more complex tasks. We will test this architecture on multimodal data like vital signs to predict patient outcomes. This project will therefore result in a powerful open-access neural network that other scientists will be able to derive for their scientific applications, along with a series of three scientific tools that will redefine the state-of-the-art in their respective fields and for which we expect a large use.
| Trustees OF Columbia University IN THE City OF NEW York | ? |
| Sorbonne Universite | 413 380 € |
https://cordis.europa.eu/project/id/101210381
Cette annonce se réfère à une date antérieure et ne reflète pas nécessairement l’état actuel. L’état actuel est présenté à la page suivante : TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK, NEW York, États-Unis.
