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)



Field: Applied Mathematics, Computation and Simulation

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