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AI.iO Artificial Intelligence in Orléans: Learning from heterogeneous data and expert knowledge. Applications in geological and environmental sciences – AI.i0 PhD Fellowship
important research environment in Artificial Intelligence (AI) with both fundamental and applied research [...] teaching in AI, Ch.A.I.R.E.-O (Chair Artificial Intelligence Research for Environment in Orléans, leader
Application of Artificial Intelligence for understanding and prediction of human and volcanic activity – AIACOPAHV
Nowadays, a key challenge in Earth observation and human behavior analysis, is data management and processing. Data acquisition of natural and human environment produces every day a large set of infor
Lorraine Artificicial Intelligence – LOR-AI
competitiveness. This project about Artificial Intelligence, led by the Université de Lorraine (UL), involves
Artificial intelligence, by the University of Bordeaux – AI by UBx
AI by UBx is a proposal of the University of Bordeaux built conjointly with the center Inria Bordeaux-Aquitaine to accelerate the ongoing development of Bordeaux as an AI reference center thanks to a
Artificial Intelligence for Health, Physical Models, Transportation and Defense – AHEAD
ty. It explores core problems in Artificial Intelligence including computer science, statistics and deep
Earth Observation with Optimal Transport for Artificial Intelligence – OTTOPIA
of data, largely under-exploited. Artificial intelligence can become a major help toward exploiting this
Intelligent Analysis and Interconnexion of Heterogeneous Contents in Digital Arenas – SourcesSay
in particular democracy and public debate, intelligently exploiting it is of crucial importance. This [...] Arena Management Systems (AMSs), a new brand of intelligent, learning-based content management systems. Users
ADvanced Submarine Intelligent Listening – ADSIL
chair opens the paradigm "ADvanced Submarine Intelligent Listening". It is headed by honorary member IUF
Low Rank Approximations for Artificial Intelligence – LoRAiA
In a context of data being collected and exploited at huge scales, designing efficient machine learning tools that capture the complexity of data is one of the most important challenges of the decade.