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Applied Mathematics, Computation and Simulation
In order to understand, analyse and predict complex meteorological, biological, physical, geological or physiological phenomena, we must first be able to describe them and simulate them using mathematical models. Inrias research teams are working to produce such models.
Stochastic Methods and Models
- ALEA - Advanced Learning Evolutionary Algorithms
- ASPI - Applications of interacting particle systems to statistics
- CQFD - Quality control and dynamic reliability
- I4S - Statistical Inference for Structural Health Monitoring
- MATHRISK - Mathematical Risk handling
- REGULARITY - Probabilistic modelling of irregularity and application to uncertainties management
- TOSCA - TO Simulate and CAlibrate stochastic models
Computational models and simulation
- BACCHUS - Parallel tools for Numerical Algorithms and Resolution of essentially Hyperbolic problems
- CAD - Computer Aided Design
- CAGIRE - Computational Approximation with discontinous Galerkin methods and compaRison with Experiments
- CALVI - Scientific computation and visualization
- CASTOR - Control, Analysis and Simulations for TOkamak Research
- COFFEE - COmplex Flows For Energy and Environment
- CONCHA - Complex Flow Simulation Codes based on High-order and Adaptive methods
- DEFI - Shape reconstruction and identification
- GAMMA3 - Automatic mesh generation and advanced methods
- IPSO - Invariant Preserving SOlvers
- MC2 - Modeling, control and computations
- MICMAC - Methods and engineering of multiscale computing from atom to continuum
- NACHOS - Numerical modeling and high performance computing for evolution problems in complex domains and heterogeneous media
- NANO-D - Algorithms for Modeling and Simulation of Nanosystems
- OPALE - Optimization and control, numerical algorithms and integration of complex multidiscipline systems governed by PDE
- POEMS - Wave propagation: mathematical analysis and simulation
- SCIPORT - Program transformations for scientific computing
- SIMPAF - SImulations and Modeling for PArticles and Fluids
- SMASH - Simulation, modeling and analysis of heterogeneous systems
Optimization, Learning and Statistical Methods
- CLASSIC - Computational Learning, Aggregation, Supervised Statistical, Inference, and Classification
- DOLPHIN - Parallel Cooperative Multi-criteria Optimization
- GEOSTAT - Geometry and Statistics in acquisition data
- MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
- MODAL - MOdel for Data Analysis and Learning
- REALOPT - Reformulations based algorithms for Combinatorial Optimization
- SELECT - Model selection in statistical learning
- SEQUEL - Sequential Learning
- SIERRA - Statistical Machine Learning and Parsimony
- TAO - Machine Learning and Optimisation
Modeling, Optimization, and Control of Dynamic Systems
- APICS - Analysis and Problems of Inverse type in Control and Signal processing
- BIPOP - Modelling, Simulation, Control and Optimization of Non-Smooth Dynamical Systems
- COMMANDS - Control, Optimization, Models, Methods and Applications for Nonlinear Dynamical Systems
- CORIDA - Robust control of infinite dimensional systems and applications
- DISCO - Dynamical Interconnected Systems in COmplex Environments
- GECO - Geometric Control Design
- MAXPLUS - Max-plus algebras and mathematics of decision
- MCTAO - Mathematics for Control, Transport and Applications
- NECS - Networked Controlled Systems
- NON-A - Non-Asymptotic estimation for online systems
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By field
- Applied Mathematics, Computation and Simulation
- Algorithmics, Programming, Software and Architecture
- Networks, Systems and Services, Distributed Computing
- Perception, Cognition, Interaction
- Computational Sciences for Biology, Medicine and the Environment
