Search for a funded project
Belief Change for Better Multi-Source Information Analysis – BE4musSIA
* Improve belief revision operators * Improve belief merging operators * Develop measures of inconsistency and measures of conflicts * Apply all of these tools to multi-source information analysis * Illustrate the tools developed in this project within on the semantic web, in order to improve qu
Towards visual reasoning in deep learning – VISA DEEP
In this AI chair, we propose to investigate tasks of visual reasoning beyond merely ImageNet classification. It is required to decline some reasoning processes in the visual analysis scheme. We intend to explore the combination of elementary reasoning blocks into deep architectures. We want to quest
Sequential and Active Learning for Optimization – SeqALO
The goal of this project is to develop a new theory of sequential and active optimization, to implement it in industrial projects, and to develop a teaching track dedicated to machine learning in general and to sequential decision theory in particular within the ENS of Lyon. Let f:X*E?R be a stoc
From local diversity to transnational institutionalization: The emergence of the European Unified Patent Court – UNIFIED
In light of the research gaps identified in the previous section, UNIFIED pursues intensive research on a first empirical case of the emergence of a unified European institution, in real time: that of institutional convergence between geographically fragmented judicial practices toward a newly born
Deep Learning for Physical Processes with applications to Earth System Science – DL4CLIM
The project builds on the complementarity of two major scientific paradigms, Physics and Machine Learning (ML). The former relies on elaborate and complex models of natural phenomena but does not offer principled methods for integrating the data generated by observation platforms (e.g. satellite) an
TopAI: Topological Data Analysis for Machine Learning and AI – TopAI
The recent years have seen all domains of science, economy and even everyday life overwhelmed by massive amounts of data. Bringing scientists and users to the most relevant, often unexpected, features and giving them the tools to discover, extract and exploit the best knowledge out of their data are
Propositional Reasoning for Large-Scale Optimization. Application to Clean Energy Mobility Issues – Massal'IA
We are in a scenario where SAT-based problem solving is highly competitive on decision problems, and Max-SAT-based approaches have been proposed for optimization problems. Max-SAT is a consolidated research line, but the performance of the solvers needs to be improved for large scale real applicatio
Unraveling the pathophysiology of Bethlem Myopathy using a unique zebrafish model for the disease – FishandCol6
BM is a muscle disease characterized by joint contractures and muscle weakness worsening with age. BM results from mutations in genes encoding one of the three a chains of collagen VI (ColVI), a component of the skeletal muscle extracellular matrix produced by interstitial fibroblasts. A still unres
Environmental ePIdemiology of COVID-19 in French Guiana: combining eDNA and biogeography to forecast future epidemiological waves – EPI-COV
Since its emergence in Wuhan, China in 2019, the speed of the spread of the Covid-19 pandemic, coupled with a lack of scientific and medical knowledge, underscores the need to improve our understanding of the epidemiological dynamics of SARS-CoV-2 within the population. In addition to the need to qu
French universities facing COVID – COVID-IN-UNI
Research on organizational crisis management focuses almost exclusively on nuclear power plants, industrial sites at risk or the reactions of public administrations to disasters. But how do organizations behave which, like universities, are characterized by functional loose coupling and weak technol
