After a final early morning run in the rising sun, reaching a point north of the city where I could see a nearby volcano (not Fuji-san!), I attended both morning on MCMC, with (again) a range of interesting, mostly novel, questions and solutions. With no overlap with his talk at mostly Monte Carlo last month, Sam Livingstone gave convincing motivations for using new tools for designing proper scaling (in the limit) for some adaptive MCMC. Charles Margossian’s talk was particularly exciting for pushing for single step MCMC when massively run in parallel, provided warm-up is over (enough). And Saif Syed discussing a new version of annealed SMC, using the variability of the estimated normalising constant as an assessment of the (although I could not catch how the tridimensional calibration was handled). I was less convinced by Kyle Kuang’s approach to overcome identifiability issues such as label switching, as it sounded too simple to be universally applicable. Bingjing Tang returned to the challenge of doubly intractable posteriors. With motivations from functional inference and a solution reminding me of noise contrastive estimation. until I spoke with the authors and realised it was much closer to our recent paper with Edoardo and Julien. While Bjorn Sprungk’s talk on Metropolized interacting particle sampling reminded me of our pinball sampler, presented… 30 years ago at the 1996 Valencia meeting! But using the product of posteriors as a target sounds suboptimal when a target that would keep particles apart (with the correct marginals) would prove more exploratory.
The noon break was the last opportunity to sample one of the food stalls in the fish market nearby, with a spicy curry udon bowl. Cutting the eel addiction!
My final session—before catching a shinkansen to Tokyo for the Information Geometry, Privacy and Monte Carlo ISBA Satellite Meeting at the Institute of Statistical Mathematics—was about loss-based posteriors, with our PhD student Shreya Roy presenting her work on prequential posteriors. And Kshitij Khare on using a loss that allows for a regular Gibbs sampler implementation via a pseudo-model and consistency properties.
This cuvée of ISBA World Meeting was exceptionally (gouleyante and) enjoyable (except for my recurrent sleeping issues) from the diverse and well-balanced programme, to the choice of plenary speakers, to the practicality of the conference centre (except for the queues for the lift!) and its location in Nagoya, with its own, unsuspected, perks! With no food poisoning this time!! ISBA 2028 is scheduled to take place in Milwaukee and I am very unlikely to attend, unless a rogue mirror pops up!
Wonderful day celebrating my long-term friend François Perron’s career, at the Université de Montréal! In full autumnal glory! 
With several long-time-no-see friends attending and presenting their work and connecting with François’ achievements, incl. Éric Marchand on Stein prediction for spherically symmetric distributions, where the predicted vector y appears in the same quadratic form as the observed one x, with the same location parameter, a setting that turns prediction into estimation of that parameter, a 
Mylène Bédard on a generalised optimal 
Yves Atchadé on 
and Alex Bouchard-Côté on escaping the curse of dimensionality by interpolations of the target, which is a variant of simulated tempering (quite the theme of the day!), and happened to be his invited lecture for the 2024 CRM-SSC prize, awarded right after. Unfortunately I had to catch my plane and face the notorious jams to the airport. (And, fortunately, I had attended Saifuddin Syed’s related 
