machine - deep learning: 13
members
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J.-D. Zucker
AI and Machine Learning for decision support tools addressing precision medicine and natural hazards issues
(Explainable Machine Learning and Agent-Based Multiscale Modelling)
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C. Selinger (CSS5 resigned 2021)
Computational and Mathematical Modelling of Multi-Strain Viral Epidemics
(stochastic simulation, machine learning, bayesian computation, graph theory)
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L. Berti-Equille
Data Quality Awareness for Computational Sustainability
(Statistical machine learning, data cleaning, probabilistic inference, data fusion, data quality, data management)
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E. Chenin
Design and Development of Integrated Research Projects on Complex Systems and Biodiversity Information
(head of the French delegation to the Global Biodiversity Information Facility (GBIF))
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J. Guérin
Developing Machine Learning Approaches to Enhance Global Resilience to Climate Change
(ML experiments design, runtime monitoring, robustness assessment, optimisation and evaluation)
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P. Larmande
Knowledge Extraction and Diffusion of Genome-Phenome Relationships in Tropical Agronomy
(semantic web and ontologies, interoperability, FAIR data portal development)
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S. Giffard-Roisin
Machine Learning for Surveillance, Understanding and Prediction of Natural Hazards
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R. Almar
Morphodynamics to Assess and Forecast Coastal Vulnerability in the Intertropical Zone
(combining applied partnership and new generation remote sensing)
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R. Hocde
Multi-Thematic Scientific Computing and Information Systems in Biological Oceanography
(Scientific diving, research cruises and IT systems development and management)
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M. Mangeas
Operational Application of Deterministic and Stochastic Mathematics to Spatio-Temporal Environment-Health Issues
(optimization, hybrid system, neural network, genetic algorithms)
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F. Niño
Processing and Dissemination of Satellite Altimetry Data for Water Resources and Coastal Management
(radar altimetry, deep learning, numerical simulation)
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M.Capello
Reconciling Exploitation and Conservation of Tropical Pelagic Ecosystems
(Derivation of alternative abundance indicators coupling operational models with fishery independant data)
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L. Drapeau
Spatial Dynamics Modelling of Natural Drivers for Socio-Ecosystems Management and Multidisciplinary Studies
(applied mathematics, spatial statistics, spatial data infrastructures)
