J
Jean-François Pradat-Peyre
Researcher at University of Paris
Publications - 36
Citations - 638
Jean-François Pradat-Peyre is an academic researcher from University of Paris. The author has contributed to research in topics: Petri net & Concurrency. The author has an hindex of 11, co-authored 35 publications receiving 542 citations. Previous affiliations of Jean-François Pradat-Peyre include Pierre-and-Marie-Curie University & Conservatoire national des arts et métiers.
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Book ChapterDOI
On Liveness and Controlled Siphons in Petri Nets
TL;DR: The controlled-siphon property is defined that generalizes the well-known Commoner's property, since it involves both traps and invariants notions, and it is proved that this property is a necessary and sufficient liveness condition for simple nets and asymmetric choice nets.
Journal ArticleDOI
Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions.
Vincent Grollemund,Pierre-François Pradat,Giorgia Querin,François Delbot,Gaétan Le Chat,Jean-François Pradat-Peyre,Peter Bede +6 more
TL;DR: A comprehensive, systematic, and critical review of ML initiatives in ALS to date and their potential in research, clinical, and pharmacological applications finds the combination of multiple clinical, biofluid, and imaging biomarkers is likely to increase the accuracy of mathematical modeling and contribute to optimized clinical trial designs.
Journal ArticleDOI
New efficient petri nets reductions for parallel programs verification
TL;DR: This paper presents new efficient Petri nets reductions based on "behavioural" reductions which preserve a fundamental property of a net and any formula of the (action-based) linear time logic that does not observe reduced transitions of the net.
Journal ArticleDOI
Development and validation of a 1-year survival prognosis estimation model for Amyotrophic Lateral Sclerosis using manifold learning algorithm UMAP.
Vincent Grollemund,Gaétan Le Chat,Marie-Sonia Secchi-Buhour,François Delbot,Jean-François Pradat-Peyre,Peter Bede,Peter Bede,Pierre-François Pradat,Pierre-François Pradat +8 more
TL;DR: This approach requires a limited set of features, is easily updated with additional patient data, and accounts for results uncertainty, as limited data availability precluded complex model designs.
Book ChapterDOI
Syntactical colored petri nets reductions
TL;DR: A syntactical version of elaborated reductions for high-level Petri nets by merging some sequential transitions into an atomic one that outperforms previous ones on a recent case study with regard both to the reduction ratio and the automatization of their application.