Point of contact
- Alexandre Chapoutot, ENSTA Paris
- Franck Delaplace, IBISC, UEVE
Summary
Mathematical modelling of systems in order to apply formal methods may involve an important amount of knowledge on the physical or biologicial process. Nowadays an important amount of data exists (coming from sensors or experiments) which can be used to define mathematical models. This represents a new challenge to apply formal methods as mathematical models coming from data do not assume particular properties.
Keywords
dynamical systems, mathematical models, data
Researchers involved or interested
- Antoine Girard, L2S, Antoine.Girard@l2s.centralesupelec.fr
- Laurent Fribourg, LSV, fribourg@lsv.ens-cachan.fr
- Goran Frehse, ENSTA Paris, goran.frehse@ensta-paris.fr
- Julien Alexandre dit Sandretto, ENSTA Paris, julien.alexandre-dit-sandretto@ensta-paris.fr
- Eric Goubault, Ecole polytechnique, goubault@lix.polytechnique.fr
- Sylvie Putot, Ecole polytechnique, Sylvie.Putot@polytechnique.edu
A few references
- Interpretable classification of time-series data using efficient enumerative techniques by Sara Mohammadinejad, Jyotirmoy V. Deshmukh, Aniruddh G. Puranic, Marcell Vazquez-Chanlatte, and Alexandre Donzé. HSCC 2020.
- Conformance verification for neural network models of glucose-insulin dynamics by Taisa Kushner, Sriram Sankaranarayanan and Marc Breton. HSCC 2020.
- Neural Predictive Monitoring by Luca Bortolussi, Francesca Cairoli, Nicola Paoletti, Scott Smolka and Scott Stoller. RV 2019.