Minus one day at BayesComp 2025! As I am attending the model misspecification satellite workshop (ten minutes late, due to repeated path finding protocol!), with an extended presentation by Jeremias Knoblauch on post-Bayesian inference, incl. powered likelihood and Gibbs posteriors. A very smooth and pedagogical presentation, esp. in the hybrid mode. A perspective I associate with the difficulties of making sense of the post-posterior, not truly a posterior, of calibrating the penalty (eg λ), picking the loss (α, β, γ divergences?) , and the drift towards learning goals since the new measure is the post-posterior predictive. Sort of paradoxical return to a Gaussian post-posterior on the parameter that does not seem to stay robust. Horrendous computational issues, when the loss itself is an integral. Use of the zig-zag sampler with an estimated unbiased gradient of the loss, much faster than pseudo-marginal, which (naïvely?) makes sense both because PDMPs directly use scores and because of the power of stochastic gradient methods. Worse perspectives for optimisation-centric posterior that are essentially vamped versions of GANs. For instance, what is the meaning of the coverage probabilities?
The second talk by Jonathan Huggins was on DC (not bagged) posteriors as martingale posteriors with m<∞ (approximating marginal distributions with random kernel MCMC—which persists in simulating the marginalised or integrated variable u from its prior, rather than adapting to the current value of the parameter θ— or subsampling MCMC akin to stochastic gradient Langevin) with connection with cut posteriors,
Then I skipped to the second workshop on Bayesian methods for distributional and semiparametric regression, to listen to my friend David Rossell’s talk on local variable selection. Which suffers more than in standard models under misspecification. Another talk involving cut posteriors, the cuts being on the spline bases…
The day and the workshop concluded with great talks by (my friends) Pierre Alquier and David Frazier. David centred his misspecification talk on cut posteriors. Managing to bring in shrinkage estimators (and mention Bill Strawderman!).
A wee stressful trip, since the races in Caen cancelled all buses and delayed the taxi enough to miss the train to Paris by 30s, catching the next available one leaving me less than one hour between the arrival of the train (delayed by construction work on the rail line) and boarding the flight at Charles de Gaulle airport, but fortunately the RER trains in Paris were running okay, there were no queues in the airport, and I thus made it in time with a bit of post-marathon jogging! (Only to be delayed at departure by one hour for stormy conditions over Germany and Austria). All this exercise proved helpful to sleep soundly and lengthily in the plane!
![Today I am tra[in]velling to Montpellier for the probability and statistics seminar of the math department (IMAG). I have not been back there since COVID, I think, and am looking forward spending some time with my friend Jean-Michel Marin.](https://i0.wp.com/xianblog.fr/wp-content/uploads/2012/02/dscn1879.jpg?resize=450%2C253&ssl=1)
On my last trip to Warwick, the local (RER) train I boarded broke on its way to the
Our trip from Paris (CDG) to Bengaluru got a wee bit (!) perturbed by 2x bad luck, with a first plane grounded for damages to a wing and a second plane flashing an alarm signal just as it was accelerating to take off, which induced an extra hour of tests, plus an unexpected long wait to get the e-visa at the Bengalore airport, resulting in an arrival in town at 5:30 am! A good thing that
I was glad to be back at the (Tata) Indian Institute of Science and its wonderful campus for the
The (touristy) train trip to Mysore was most pleasant, on an air-conditioned carriage with food vendors proposing their wares all along the journey, great views of the countryside and an arrival sharp on time. The reverse trip to the airport was less successful as the 
