Archive for manifold exploration

Approximation Methods in Bayesian Analysis [#3]

Posted in Mountains, pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , on June 23, 2023 by xi'an

My last day (#4) at the workshop, as I had to return to Paris earlier. A rather theoretical morning again, with Morgane Austern on (probabilistic) concentration inequalities on transport distances, far from my comfort zone if lively, Jason Xu on replacing non-convex penalisation factors to distances to the corresponding manifold, which I found most interesting if not directly helpful for simulating over submanifolds, and Hugo Lavenant on studying the impact of prior choice as merging of opinions, in the (Milanese) setting of completely random measures, with the surprise occurrence of a double bent for some choices. The afternoon session saw Andrew Gelman reflecting on multiscale modelling (sans slide et sans tableau) and Chris Holmes introduce the fundamentals of Bayesian conformal prediction, towards reaching well-calibrated (in a frequentist sense) Bayesian procedures by resorting to exchangeability and rank tests. I alas missed the other talks of the day.

In recap, this was a wonderful conference, with a perfect audience size, a diverse if intense program, and a lot of interactions. In addition, the short talk sessions worked very nicely, even at 22:10 after a long day. And attracted very strong audience, even at 22:10! Indeed, they were uniformly well-calibrated, time-wise, and with high clarity messages. To be repeated. As there were many newcomers to CIRM, they discovered the idiosyncrasies of the place and of its surrounding, mostly positively.

On the outdoor front, the week saw an overall moderately hot weather but a constant wind that prevented me from sleeping (well), but which helped with waking up before dawn to cycle or run to my open water pool! The sea remained reasonably choppy, so waves did not prevent my swimming.

advancements in Bayesian methods and implementations

Posted in Books, Statistics, University life with tags , , , , , , , , on November 10, 2022 by xi'an

The handbook of (recent) advances in Bayesian methods is now out (at the Elsevierian price of $250!) with chapters on Gibbs posteriors [Ryan Martin & Nicolas Syring], martingale distributions [Walker], selective inference [Daniel García Racines & Alastair Young], manifold simulations [Sumio Watanabe], MCMC for GLMMs [Vivek Roy] and multiple testing [Noirrit Chandra and Sourabh Bhattacharya]. (Along with my chapter on 50 shades of Bayesian testing.) Celebrating 102 years for C.R. Rao, one of the three editors of this volume (as well as the series) along with Arni Srivastava Rao and Alastair Young.

MCqMC 2014 [day #4]

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , on April 11, 2014 by xi'an

Leuven7

I hesitated in changing the above title for “MCqMSmaug” as the plenary talk I attended this morning was given by Wenzel Jakob, who uses Markov chain Monte Carlo methods in image rendering and light simulation. The talk was low-tech’, with plenty of pictures and animations (incl. excerpts from recent blockbusters!), but it stressed how much proper rending relies on powerful MCMC techniques. One point particularly attracted my attention, namely the notion of manifold exploration as it seemed related to my zero measure recent post. (A related video is available on Jakob’s webpage.) You may then wonder where the connection with Smaug could be found: Wenzel Jakob is listed in the credits of both Hobbit movies for his contributions to the visual effects! (Hey, MCMC made Smaug [visual effects the way they are], a cool argument for selling your next MCMC course! I will for sure include a picture of Smaug in my next R class presentation…) The next sessions of the morning opposed Sobol’s memorial to more technical light rendering and I chose Sobol, esp. because I had missed Art Owen’s tutorial on Sunday, as he gave a short presentation on using Sobol’s criteria to identify variables contributing the most to the variability or extreme values of a function, an extreme value kind of ANOVA, most interesting if far from my simulation area… The afternoon sessions saw MCMC talks by Luke Bornn and Scott Schmidler, both having connection with the Wang-Landau algorithm. Actually, Scott’s talk was the one generating the most animated discussion among all those I attended in MCqMC! (To the point of the chairman getting rather rudely making faces…)