Today is the launching day of PRAIRIE, one of the four Instituts Interdisciplinaires d’Intelligence Artificielle (3IA) supported by the French government. Taking place in Paris Dauphine, with Yann Le Cun as guest speaker. I have been fortunate to be endowed with one of these chairs for the coming years, along with my CEREMADE colleagues Laurent Cohen and Irène Waldspurger.
The post-doctoral position supported by the ANR funding of our Paris-Saclay-Montpellier research conglomerate on approximate Bayesian inference and computation remains open for the time being. We are more particularly looking for candidates with a strong background in mathematical statistics, esp. Bayesian non-parametrics, towards the analysis of the limiting behaviour of approximate Bayesian inference. Candidates should email me (gmail address: bayesianstatistics) with a detailed vita (CV) and a motivation letter including a research plan. Letters of recommendation may also be emailed to the same address.
Four French institutes have just been selected by [the jury mandated by] the French Government to become interdisciplinary institutes for artificial intelligence (3IA):
• ANITI (Toulouse), centred at l’Université Fédérale Toulouse Midi-Pyrénées
• MIAI @ Grenoble Alpes (Grenoble), centred at l’Université Grenoble Alpes
• PRAIRIE (Paris), centred à Inria
• 3IA Côte d’Azur (Nice), centred at l’Université Côte d’Azur
with Paris Dauphine, PSL Research University, a component of the third institute. (Where Prairie stands for PaRis Artificial Intelligence Research InstitutE.) This follows the “plan Villani“, launched by Cédric Villani to boost research in artificial intelligence in France and [possibly] slow down the brain drain of French IA researchers. With individual chairs attribued to each project, soon to be announced.
Two of my colleagues [and co-authors] at Dauphine, Elyès Jouini and Clotilde Napp, published a paper in Science last week (and an associated tribune in Le Monde which I spotted first) about explaining differences in national gender inequalities in maths (as measured by PISA) in terms of the degree of overall inequality in the respective countries. Gaps in the highest maths performer sex ratio. While I have no qualm about the dependency or the overall statistical cum machine learning analysis (supported by our common co-author Jean-Michel Marin), and while I obviously know nothing about the topic!, I leisurely wonder at the cultural factor (which may also partly explain for the degree of inequality) when considering that the countries at the bottom of the above graphs are rather religious (and mostly catholic). I also find it most intriguing that the gender gap is consistently reversed when considering higher performer sex ratio for reading, because mastering the language should be a strong factor in power structures and hence differences therein should also lead to inequalities…
 | xi'an on sampling the mean |
| sampling the mean -… on sampling the mean | |
 | João Neto on sampling the mean |
| sampling the mean… on sampling the mean | |
 | Pierre Jacob on unbiased MCMC discussed at the… |
