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EXPlainable artificial intelligence: a KnowlEdge CompilaTion FoundATION
The EXPEKCTATION project is about explainable and robust AI. It aims to devise global model-agnostic approaches for interpretable and robust machine learning using knowledge compilation: we seek for g
Green Artificial Intelligence
In recent years, artificial intelligence (AI) has become increasingly intertwined with our daily lives. However, AI such as that currently supported by most major players in the industry like GAFAM, i
Stattistics, computation and Artificial Intelligence
The key factor for the recent boom in AI is the emergence of deep learning (DL). The successes of these methods - in particular, for supervised learning- are amazing. But the limits and some of the do
TopAI: Topological Data Analysis for Machine Learning and AI
TopAI is a project that aims at developing a world-leading research activity on topological and geometric approaches in Machine Learning (ML) and Artificial Intelligence (AI) going from mathematical f
Wide exploration of genetic diversity in Brassica species for sustainable crop production
The identification of new variability represents a major tool to face challenges to overcome global warming and improve farming system sustainability. Turnips and cabbages, which largely contribute to
Camel breeding systems: actors in the sustainable economic development of the northern Sahara territories through innovative strategies for natural resource management and marketing
Marginal in the Maghreb and even more globally, camel breeding systems remain important in desert areas not only from cultural and identity perspectives but also as important economic asset. Moroccan
Bridging Statistical and Computational efficiency in Artificial Intelligence
With the enormous amounts of data involved in training a machine learning system, as well as the trend to push artificial intelligence to mobile devices and embedded systems, taking into account compu
Advanced Machine/Deep learning for Heterogeneous Large scale data
Professor M. Vazirgiannis is involved in data science research since the 1990’s, worked in different research areas of this domain maintaining significant scientific impact. He established and leads t
HUman-MAchine Affective INteraction & Ethics
Abstract: The new uses of affective social robots, conversational agents, and the so-called “intelligent” systems, in fields as diverse as health, education or transport reflect a phase of significant
Deep Learning for Physical Processes with applications to Earth System Science
Motivations and Scientific Program: the project targets the development of Deep Learning (DL) methods for the modeling of physical processes. The application domain is environment and climate. It buil
