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2017 Project-Team Activity Report
MISTIS
Modelling and Inference of Complex and Structured Stochastic Systems
Research centre:
Grenoble - Rhône-Alpes
In partnership with: Institut polytechnique de Grenoble, Université de Grenoble Alpes
In collaboration with: Laboratoire Jean Kuntzmann (LJK)
In collaboration with: Laboratoire Jean Kuntzmann (LJK)
Field: Applied Mathematics, Computation and Simulation
Theme: Optimization, machine learning and statistical methods
Theme: Optimization, machine learning and statistical methods
Keywords:
Computer Science and Digital Science:
- A3.1.1. - Modeling, representation
- A3.1.4. - Uncertain data
- A3.3.2. - Data mining
- A3.3.3. - Big data analysis
- A3.4.1. - Supervised learning
- A3.4.2. - Unsupervised learning
- A3.4.4. - Optimization and learning
- A3.4.5. - Bayesian methods
- A3.4.7. - Kernel methods
- A5.3.3. - Pattern recognition
- A5.9.2. - Estimation, modeling
- A6.2. - Scientific Computing, Numerical Analysis & Optimization
- A6.2.3. - Probabilistic methods
- A6.2.4. - Statistical methods
- A6.3. - Computation-data interaction
- A6.3.1. - Inverse problems
- A6.3.3. - Data processing
- A6.3.5. - Uncertainty Quantification
- A9.2. - Machine learning
- A9.3. - Signal analysis
Other Research Topics and Application Domains:
- B1.2.1. - Understanding and simulation of the brain and the nervous system
- B2.6.1. - Brain imaging
- B3.3. - Geosciences
- B3.4.1. - Natural risks
- B3.4.2. - Industrial risks and waste
- B3.5. - Agronomy
- B5.1. - Factory of the future
- B9.4.5. - Data science
- B9.9.1. - Environmental risks