Publications (24)
Analyzing Stochastic Computer Models: A Review with Opportunities
Evan Baker, Pierre Barbillon, Arindam Fadikar +10
In modern science, computer models are often used to understand complex phenomena, and a thriving statistical community has grown around analyzing them. This review aims to bring a…
Learning common structures in a collection of networks. An application to food webs
Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet
Let a collection of networks represent interactions within several (social or ecological) systems. We pursue two objectives: identifying similarities in the topological structures…
HyperSBINN: A Hypernetwork-Enhanced Systems Biology-Informed Neural Network for Efficient Drug Cardiosafety Assessment
Inass Soukarieh, Gerhard Hessler, Hervé Minoux +6
Mathematical modeling in systems toxicology enables a comprehensive understanding of the effects of pharmaceutical substances on cardiac health. However, the complexity of these mo…
Sensitivity analysis of spatio-temporal models describing nitrogen transfers, transformations and losses at the landscape scale
Jordi Ferrer Savall, Damien Franqueville, Pierre Barbillon +5
Modelling complex systems such as agroecosystems often requires the quantification of a large number of input factors. Sensitivity analyses are useful to determine the appropriate…
Parametric estimation of complex mixed models based on meta-model approach
Pierre Barbillon, Célia Barthélémy, Adeline Samson
Complex biological processes are usually experimented along time among a collection of individuals. Longitudinal data are then available and the statistical challenge is to better…
Common Structure Discovery in Collections of Bipartite Networks: Application to Pollination Systems
Louis Lacoste, Pierre Barbillon, Sophie Donnet
Bipartite networks are widely used to encode the ecological interactions. Being able to compare the organization of bipartite networks is a first step toward a better understanding…