About us

History & People

This project, and the code related, were started in 2007 at CERFACS under the name JPOD (Jack Proper Orthogonal Decomposition) by T. Braconnier and M. Ferrier, which were supervised by J-C. Jouhaud and J-F. Boussuge. During 5 years, the code has been successfully tested and validated on industrial configurations during the European SimSAC and ALEF (FP7) projects. Then, the project has been dormant untill 2015 when Romain Dupuis (PhD student supervised by J-C. Jouhaud) started to be interested in Surrogate Models for aerothermal predictions. After that, in 2016, Uncertainty Quantification capabilities were added by Pamphile Roy (PhD student supervised by B. Cuenot, S. Ricci and J-C. Jouhaud) leading to the new name: BATMAN, which stands for Bayesian Analysis Tool for Modeling and uncertAinty quaNtification. On November, 23th 2017 the UQ team of Cerfacs have decided to release the code on GitLab as open-source under the CECILL-B free software license agreement.

The following people have been core contributors to batman’s development and maintenance:

  • Pamphile Roy,
  • Romain Dupuis,
  • Jean-Christophe Jouhaud,
  • Sophie Ricci,
  • Robin Campet,
  • Cyril Fournier,
  • Thierry Braconnier (JPOD),
  • Marc Ferrier (JPOD).

Note

Please do not email the authors directly to ask for assistance or report issues.

See also

How you can contribute to the project

Citing batman

If you use batman in a scientific publication, we would appreciate citations to the following paper:

BATMAN: Statistical analysis for expensive computer codes made easy, Roy, P.T. et al., JOSS, 2018.

Bibtex entry:

@article{batman_paper,
 title={BATMAN: Statistical analysis for expensive computer codes made easy},
 author={Roy, P.T. and Ricci, S. and Dupuis, R. and Campet, R., and
 Jouhaud, J.-C. and Fournier, C.},
 journal={The Journal of Open Source Software},
 doi={10.21105/joss.00493},
 year={2018}
}

If you want to cite batman for an application, you may also want to consider:

Comparison of Polynomial Chaos and Gaussian Process surrogates for uncertainty quantification and correlation estimation of spatially distributed open-channel steady flows, Roy, P.T. et al., SERRA, 2017.

Bibtex entry:

@article{batman_appli,
 title={Comparison of Polynomial Chaos and Gaussian Process surrogates for
 uncertainty quantification and correlation estimation of spatially
 distributed open-channel steady flows},
 author={Roy, P.T. and El Moçaïd, N. and Ricci, S. and Jouhaud, J.-C. and
 Goutal, N. and De Lozzo, M. and Rochoux M.C.},
 journal={Stochastic Environmental Research and Risk Assessment},
 doi={10.1007/s00477-017-1470-4},
 year={2017}
}