**W**hen I got invited to BAYSM’14 last December, I was quite excited to be part of the event. (And to have the opportunities to be in Austria, in Wien and on the new WU campus!) And most definitely and a posteriori I have not been disappointed given the high expectations I had for that meeting…! The organisation was seamless, even by Austrian [high] standards, the program diverse and innovative, if somewhat brutal for older Bayesians and the organising committee (Angela Bitto, Gregor Kastner, and Alexandra Posekany) deserves an ISBA recognition award [yet to be created!] for their hard work and dedication. Thanks also to Sylvia Früwirth-Schnatter for hosting the meeting in her university. They set the standard very high for the next BAYSM organising team. (To be hold in Firenze/Florence, on June 19-21, 2016, just prior to the ISBA World meeting *not* taking place in Banff. A great idea to associate with a major meeting, in order to save on travel costs. Maybe the following BAYSM will take place in Edinburgh! Young, local, and interested Bayesians just have to contact the board of BAYS with proposals.)

So, very exciting and diverse. A lot of talks in applied domains, esp. economics and finance in connection with the themes of the guest institution, WU. On the talks most related to my areas of interest, I was pleased to see Matthew Simpson working on interweaving MCMC with Vivek Roy and Jarad Niemi, Madhura Killedar constructing her own kind of experimental ABC on galaxy clusters, Kathrin Plankensteiner using Gaussian processes on accelerated test data, Julyan Arbel explaining modelling by completely random measures for hazard mixtures [and showing his filliation with me by (a) adapting my pun title to his talk, (b) adding an unrelated mountain picture to the title page, (c) including a picture of a famous probabilist, Paul Lévy, to his introduction of Lévy processes and (d) using xkcd strips], Ewan Cameron considering future ABC for malaria modelling, Konstantinos Perrakis working on generic importance functions in data augmentation settings, Markus Hainy presenting his likelihood-free design (that I commented a while ago), Kees Mulder explaining how to work with the circular von Mises distribution. Not to mention the numerous posters I enjoyed over the first evening. And my student Clara Grazian who talked about our joint and current work on Jeffreys priors for mixture of distributions. Whose talk led me to think of several extensions…

Besides my trek through past and current works of mine dealing with mixtures, the plenary sessions for mature Bayesians were given by Mike West and Chris Holmes, who gave very different talks but with the similar message that data was catching up with modelling and with a revenge and that we [or rather young Bayesians] needed to deal with this difficulty. And use approximate or proxy models. Somewhat in connection with my last part on an alternative to Bayes factors, Mike also mentioned a modification of the factor in order to attenuate the absorbing impact of long time series. And Chris re-set Bayesian analysis within decision theory, constructing approximate models by incorporating the loss function as a substitute to the likelihood.

Once again, a terrific meeting in a fantastic place with a highly unusual warm spell. Plus enough time to run around Vienna and its castles and churches. And enjoy local wines (great conference evening at a Heuriger, where we did indeed experience Gemütlichkeit.) And museums. Wunderbar!