Archive for machine learning

AstroDeep in Paris [postdoc position]

Posted in Kids, Statistics, Travel, University life with tags , , , , , , on November 13, 2021 by xi'an

Here is a call for candidates to a postdoc on Bayesian machine learning methods for measuring weak gravitational lensing.  In downtown Paris. There is no application deadline, which means the earlier the application the better!

The candidate should hold a PhD in mathematics, computer science, physics/astrophysics or engineering. Candidates with either a scientific or technical background are welcome to apply. Prior experience in machine learning and Bayesian statistics would be an asset. Our group is committed to diversity and equality, and encourage applications from women and underrepresented minorities. We support a flexible and family-friendly work environment. The position includes an internationally competitive salary and generous travel budget. French language skills are not required. Applicants should send a CV and research statement, and arrange for three reference letters to be sent to the contact email address

Choose France – CNRS AI Rising Talents Programme for exceptionally talented early-career AI researchers

Posted in pictures, Travel, University life with tags , , , , , , , , , on October 29, 2021 by xi'an

The French national scientific research institute, CNRS, is launching a one-shot call for hiring early-career  AI researchers on a 5 year 100% research position in any of the CNRS research units in France. Including ours in Paris Dauphine. The offer is quite generous in that the attached grant provides a full professor salary and support to hire postdocs and PhD students. Early career means two to seven years after PhD. The deadline is 30 November.

reproducibility check [Nature]

Posted in Statistics with tags , , , , , , , , on September 1, 2021 by xi'an

While reading the Nature article Swarm Learning, by Warnat-Herresthal et [many] al., which goes beyond federated learning by removing the need for a central coordinator, [if resorting to naïve averaging of the neural network parameters] I came across this reporting summary on the statistics checks made by the authors. With a specific box on Bayesian analysis and MCMC implementation!

ISBA 2021 grand finale

Posted in Kids, Mountains, pictures, Running, Statistics, Travel, University life, Wines with tags , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , on July 3, 2021 by xi'an

Last day of ISBA (and ISB@CIRM), or maybe half-day, since there are only five groups of sessions we can attend in Mediterranean time.

My first session was one on priors for mixtures, with 162⁺ attendees at 5:15am! (well, at 11:15 Wien or Marseille time), Gertrud Malsiner-Walli distinguishing between priors on number of components [in the model] vs number of clusters [in the data], with a minor question of mine whether or not a “prior” is appropriate for a data-dependent quantity. And Deborah Dunkel presenting [very early in the US!] anchor models for fighting label switching, which reminded me of the talk she gave at the mixture session of JSM 2018 in Vancouver. (With extensions to consistency and mixtures of regression.) And Clara Grazian debating on objective priors for the number of components in a mixture [in the Sydney evening], using loss functions to build these. Overall it seems there were many talks on mixtures and clustering this year.

After the lunch break, when several ISB@CIRM were about to leave, we ran the Objective Bayes contributed session, which actually included several Stein-like minimaxity talks. Plus one by Théo Moins from the patio of CIRM, with ciccadas in the background. Incredibly chaired by my friend Gonzalo, who had a question at the ready for each and every speaker! And then the Savage Awards II session. Which ceremony is postponed till Montréal next year. And which nominees are uniformly impressive!!! The winner will only be announced in September, via the ISBA Bulletin. Missing the ISBA general assembly for a dinner in Cassis. And being back for the Bayesian optimisation session.

I would have expected more talks at the boundary of BS & ML (as well as COVID and epidemic decision making), the dearth of which should be a cause for concern if researchers at this boundary do not prioritise ISBA meetings over more generic meetings like NeurIPS… (An exception was George Papamakarios’ talk on variational autoencoders in the Savage Awards II session.)

Many many thanks to the group of students at UConn involved in setting most of the Whova site and running the support throughout the conference. It indeed went on very smoothly and provided a worthwhile substitute for the 100% on-site version. Actually, I both hope for the COVID pandemic (or at least the restrictions attached to it) to abate and for the hybrid structure of meetings to stay, along with the multiplication of mirror workshops. Being together is essential to the DNA of conferences, but travelling to a single location is not so desirable, for many reasons. Looking for ISBA 2022, a year from now, either in Montréal, Québec, or in one of the mirror sites!

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