Many works of this research group have led to actionable implementations for imputation, estimation, and prediction with incomplete data that are mostly available in R.
For a comprehensive overview of missing values problems and methods
in R and in python we refer to our platform R-miss-tastic (established
with Nathalie Vialaneix
and Nicholas Tierney).
Related to this platform is the CRAN Task
View on Missing Data maintained by members of this group and
Nathalie Vialaneix.
R-packages developed by former and current group members:
Other implementations developed inside our group:
Several implementations have been proposed by members of this group to tackle treatment effect estimation with incomplete attributes and on combined experimental and observational data:
Additionally, we have created the CRAN Task View on Causal Inference (maintainers: Pan Zhao, Imke Mayer, et al.). It provides an overview of implementations of causal inference and causal discovery methods currently available on CRAN (The Comprehensive R Archive Network). If you are intersted in contributing or have feedback on this task view, please reach out to the task view maintainers.
Numerous endeavors from this research group have resulted in practical applications for uncertainty quantification techniques, including the development of methodologies in conformal prediction.
ICUBAM provides real-time monitoring of intensive care unit (ICU)
bed availability in French hospitals. Data is directly obtained from
doctors working inside ICU by sending them SMS with a HTTP link to a
form that they can fill in 15 seconds.
The project was
co-built by ICU Doctors from CHRU Nancy/Université de Loraine and
engineers from INRIA & Polytechnique. It was fleshed out live during
the Covid crisis in Eastern France to answer an urgent need for finding
available ICU beds in a saturated and deteriorating situation. At the
time of writing, 5 engineers are working full-time, 7 days a week, on
the project, in direct contact with the team of ICU doctors on the
ground.