Archive for sunset
last sunset on the roaring twenties
Posted in Kids, pictures, Running, Travel with tags 30th birthday, beach, Marseille, Méditerranée, Plage des Catalans, summer light, sunset on September 2, 2026 by xi'an
watching the eclipse
Posted in Kids, pictures, Running, Travel with tags 20h17, eclipse, ghost image, jatp, Parc de Sceaux, Sceaux, solar eclipse, sunset on August 21, 2026 by xi'an
approximately Bayes [on Skye]
Posted in Mountains, pictures, Running, Statistics, Travel, University life with tags abseiling, Aussois, BayesComp 2025, BayesComp 2027, Bayesian predictive, climbing, cold water swimming, Cuillin ridge, deep neural network, Gaelic college, Gibbs priors, haggis, Highlands, jatp, Loch Hourne, martingale posterior, munroes, nested sampling, post-Bayes inference, road race, Robert Burns, Sabhal Mor Ostaig, safe Bayes, Scotland, sunset, the inaccessible pinacle, The North, transformer, uncertainty assesment on May 28, 2026 by xi'an
Wow, what an exciting workshop in an equally exciting place! Strong themes were post-Bayes (Gibbs priors, martingale priors, predictive Bayes, &tc.) and deep neural network modelling. With animated discussions allowed by the free windows planned in the program. And the very early dinner at Sabhal Mòr Ostaig that let a long sunlit evening for impromptu Q&A’s [with a serving of lamb and another of haggis pie!]. Making me realise the large corpus of work I had missed in the past years on these topics, even though the satellite of BayesComp last year was already an eye opener. (Stay tuned for news about BayesComp 2027 & its mirror in Aussois!) The proposal in Jeff Miller’s discussion of Jeremias Knoblauch’s overview of post-Bayes [I’d rather favour another name!] to consider directly likelihood values as the data was particularly appealing to me, while reminding me of the foundations of nested sampling. (Hopefully, a new perspective on uncertainty assessment for nested sampling is soon to be completed!)
On the non-academic side, the long days in The North helped with my running with above 90km bagged in the week (and no downpour on the runs). But little to my swimming since the water was cold enough to limit my laps to 5mn each time! Paradoxically the worst day was the one I chose for climbing the Inaccessible Pinnacle (as expanded in another ‘Og entry).
optimal sampling for kernel quadrature on unbounded domains
Posted in Books, Statistics, University life with tags Bayesian quadrature, bois de Boulogne, contraction rate, ERC Synergy Grant, Gaussian processes, minimaxity, Monte Carlo integration, numerical integration, Ocean, probabilistic integration, probabilistic numerics, RKHS, sunset, uncertainty quantification, Université Paris Dauphine on May 22, 2026 by xi'an
My PhD student Edoardo Bandoni, along with Julien Stoehr and myself, completed a paper on validating (Bayesian) kernel quadrature with unbounded domains of integration. Which connects with probabilistic numerics, since the integrand is modelled as a Gaussian process. And RKHS methods. As opposed to Monte Carlo estimators, quadrature methods approximate integrals of smooth functions with worst-case error decaying at a minimax rate α/d for smoothness α in dimension d. Existing rate-optimal quadrature methods often depend on deterministic point sets tailored to a specific kernel, making them sensitive to misspecification and thus less robust in practice. This paper studies instead randomised quadrature methods, with a focus on robustness rather than on kernel-specific optimality. We construct an explicit, n-dependent, sampling distribution that achieves minimax rates for worst-case errors over smoothness classes without requiring knowledge of the kernel. This kernel-agnostic design does improve robustness while retaining optimal rates and extends Briol et al. (2019) to the unbounded case. Which cannot always be easily handled by a change of variables. Our result thus mostly covers unbounded sampling measures such as Gaussian and Student-t distributions, extending beyond compact domains. The results provide both theoretical guarantees and a practical recipe for robust, rate-optimal, randomised quadrature. [The above is mostly stated in the abstract.]
glorious morn on Loch Hourn [jatp]
Posted in Mountains, pictures, Travel, University life with tags approximate Bayesian inference, approximately Bayes, Eilean Sgitheanach, Frances Walker, Gaelic college, ICMS, Inner Hebrides, Isle of Skye Brewery, Sabhal Mor Ostaig, Scotland, Scottish Gaelic, sunset, worksho on May 19, 2026 by xi'an
