A more theoretical Day #2 of the workshop, with Debdeep Pati comparing two representations of Gaussian processes with significantly different efficiencies, and Aad van der Vaart presenting a form of linearisation for a range of inverse problems, Kolyan Ray debiasing Lasso impacts by variational Bayes, although through a somewhat intricate process that distanced the procedure from Bayesian grounds imho, Judith Rousseau (Dauphine) also drifting away from Bayesian canons by looking anew at empirical Bayes with surprising differences from genuine B analysis, connecting with the cutoff phenomenon she and Kerrie exhibited in their 2011 mixture paper, as well as labelling the marginal likelihood a misspecified model. Trevor Campbell and Sinead Williamson both provided Bayesian perspectives on normalising flows, in particular the impact of computer imprecision on reversibility, leading to the notion of shadow paths (screenshot below), while Giovanni Rebaudo talked about mixtures supported by trees, a fascinating object!
On Day #3, Marc Beaumont talked on a mixture of composite likelihood à la Ryden, making me wonder of optimisation of blocks for HMC? EP-ABC, with the issue of the unknown amount of approximation, and adaptivity?, Maria de Iorio presented work on finite and infinite mixtures with repulsive (Coulomb) priors, achieving a unified framework, plus known evidence (?), with a correlated talk by Federico Camerlenghi in the afternoon, with novel notions (for me) of Palm measures and calculus, and another correlated talk by María-Fernanda Gil Leyva Villa, on stick-breaking processes for species sampling with dependent length variables, with related improvements in Gibbs implementation (screenshot below).
This was followed by two theoretical talks on continuous time processes by Paul Jenkins (Warwick) on the fine properties of the Flemming-Viot process, with mentions of Don Dawson’s results reminding me of the 1988 and 1989 summers I spent at Carleton University, where he was located at the time, and Matteo Ruggieri, with the novel (to me) notion of dual Markov processes that could prove useful in a lot of latent variable models. Fabrizio Leisen expanded on his early work on partial exchangeability and Steve MacEachern on dependent quantile pyramids, which relate to quantile regression, a constant source of puzzlement for me. Motivating the perspective by robustness and misspecification arguments. But I am a wee bit puzzled by the distinction between quantile pyramids and other non-parametric solutions.
On the outdoor front (in early mornings), choppy waters at sea (in the Sugiton calanque, pictured above) thanks to the endless mistral wind, nice run down from Mont Puget with friends, limited utility of my rented mountain bike (except to reach the nearest supermarket, 3km away)
Þe first internal research workshop of our ERC Synergy project OCEAN is taking place in Les Houches, French Alps, this coming week with 15 researchers gathering for brain-storming on some of the themes at the core of the project, like algorithmic tools for multiple decision-making agents, along with Bayesian uncertainty quantification and Bayesian learning under constraints (scarcity, fairness, privacy). Due to the small size of the workshop (which is perfect for engaging into joint work), it could not be housed by the nearby, iconic, École de Physique des Houches but will take place instead in a local hotel.
On the leisurely side, I hope there will be enough snow left for some lunch-time ski breaks [with no bone fracture à la Adapski!] Or, else, that the running trails nearby will prove manageable.
In connection with the 
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