Become a sponsor to Robin Thibaut
About
I am a PhD Fellow at Ghent University, Belgium. My research focuses on developing a new framework for experimental design in earth sciences under a Bayesian approach. I have experience in marine geophysical surveys, near-surface geophysics and coding. My research interests include Bayesian statistics, geostatistics, image processing, data science, and machine learning. I am interested in applying these methods to a variety of problems in environmental sciences and earth sciences.
Latest papers
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection area
https://doi.org/10.1016/j.jhydrol.2021.126903
- Official repository: skbel
A new workflow to incorporate prior information in minimum gradient support (MGS) inversion of electrical resistivity and induced polarization data.
https://doi.org/10.1016/j.jappgeo.2021.104286
- Official repository: MGS-public
Research
Let's connect!
Featured work
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scikit-learn/scikit-learn
scikit-learn: machine learning in Python
Python 60,248 -
scikit-fmm/scikit-fmm
scikit-fmm is a Python extension module which implements the fast marching method.
Python 275 -
robinthibaut/pysgems
Use SGeMS (Stanford Geostatistical Modeling Software) within Python.
Python 46 -
robinthibaut/skbel
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
Python 22
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