Archive for ICSDS 2025
calle naranja en sevilla [jatp]
Posted in pictures, Running, Travel, University life with tags Andalucía, home cooking, ICSDS 2025, jatp, orange tree, Sevilla, Spain on January 8, 2026 by xi'an
Avancia, Botani, Tarantelo, Sacrima, y Sauterne
Posted in Statistics with tags aceites, Andalucía, Az Zait, Cadiz, Chardonnay, Galicia, godillo, ICSDS 2025, Jerez, Malaga, mencíá, moscatel, muscat, organic wine, Sauternes, Sevilla, Spain on December 20, 2025 by xi'an
a (sunny, crisp) day at ICSDS 2025
Posted in pictures, Running, Statistics, Travel, University life with tags 5thSYSORM, AI, Andalucía, Bayesian nonparametrics, Bill Strawderman, conferences, CRiSM, Croatia, deviance information criterion, DIC, ellipsoid, generalised Bayesian inference, Guadalquivir, ICSDS 2025, ICSDS 2026, IMS, martingale posterior, minimaxity, prediction, Réal Fabrica deTabacos de Sevilla, Sevilla, shrinkage, shrinkage estimation, Spain, Split, transformer, Universidad de Sevilla, University of Warwick, urn on December 19, 2025 by xi'an
While my first day at ICSDS 2025 was somewhat hectic, having realised late the night before that I was giving a talk!—I had forgotten I had submitted a title at registration time and never received any communication from the organisers, including (or excluding) a request for an abstract. I thus hastily updated my November talk in Sevilla for my December talk in Sevilla! but paid less attention than needed to the sessions I attended—, Wednesday was more peaceful—esp. after a 16K run along the Guadalquivir—and I engaged into two great Bayesian learning sessions, one that seemed designed for me!, involving my (40y long friend) Ed George on his latest result on proper prior minimaxity and shrinkage, with our late friend Bill Strawderman as a co-author since they worked on the problem prior to Bill’s demise, Charles Margossian on variational inference preserving some symmetries in the target and hence keeping the same statistics, with elliptically symmetric families, and Fletcher Christensen on DIC for some mixed models, with references to our “DIC’s eights” paper (but still picking one version of DIC in the end!)
The second session was on prediction learning!—with me as the chair, as I realized one minute before! AI !—with (my friend) Veronika Rockova using AI predictions as a prior predictive and connecting them with Bayesian nonparametrics, Kenyon Ng (who visited me last Spring) on a similar approach using pretrained transformers like TabPFN and martingale posterior inference, Lorenzo Cappello in a generalisation of martingale prediction and Andrea Ghiglietti on the mathematics of an involved urn system.
The afternoon session was a plenary talk by Daniela Witten in the magnificent building of the Real Fabrica de Tabacos, but the room was unfortunately too small for the audience and I could not enter. Hopefully her talk will have a significant intersection with the CRiSM colloquium she delivers in Warwick late January. I thus walked around the old town till the following poster session, held in the Real Fabrica courtyard, under the sun. As I got involved into a deep discussion of the relevance of mirror meetings (which I defend!) versus the dangers on principal (parent) conferences (which can be mitigated by the mirror conference participants registering, to some extent, for the principle one)—more to come on the ‘Og and in the ISBA Bulletin!—, I did not peruse the available posters, sorry…
And, by the way, the conference organisers also revealed the location of ICSDS 2026 which is Croatia, my first bet! In the city of Split we visited in 2023.
prequential posteriors
Posted in Books, Statistics, University life with tags arXiv, Bayesian deep learning, data generating process, generalised Bayesian inference, ICSDS 2025, IMS, intractable likelihood, PhD students, prequential loss, probabilistic forecasting, Sevilla, SMC, Student Award, University of Warwick on December 15, 2025 by xi'an
Data assimilation is a fundamental task in updating forecasting models upon observing new data, with applications ranging from weather prediction to online reinforcement learning. Deep generative forecasting models (DGFMs) have shown excellent performance in these areas, but assimilating data into such models is challenging due to their intractable likelihood functions. This limitation restricts the use of standard Bayesian data assimilation methodologies for DGFMs. To overcome this, we introduce prequential posteriors, based upon a predictive-sequential (prequential) loss function; an approach naturally suited for temporally dependent data which is the focus of forecasting tasks. Since the true data-generating process often lies outside the assumed model class, we adopt an alternative notion of consistency and prove that, under mild conditions, both the prequential loss minimizer and the prequential posterior concentrate around parameters with optimal predictive performance. For scalable inference, we employ easily parallelizable wastefree sequential Monte Carlo (SMC) samplers with preconditioned gradient-based kernels, enabling efficient exploration of high-dimensional parameter spaces such as those in DGFMs. We validate our method on both a synthetic multi-dimensional time series and a real-world meteorological dataset; highlighting its practical utility for data assimilation for complex dynamical systems.
¡Vuelo a Sevilla otra vez!
Posted in pictures, Statistics, Travel, University life, Wines with tags 2025 IMS International Conference on Statistics and Data Science, Andalucía, conference, Croatia, Greece, ICSDS 2025, IMS, Institute of Mathematical Statistics, Jerez, mathematical statistics, Mediterranean Sea, Sevilla, Spain, Turkey on December 14, 2025 by xi'an
