Archive for Engineering

夢幻花 [Dream flower]

Posted in Statistics with tags , , , , , , , , , , , on January 18, 2020 by xi'an

Another Japanese mystery novel by Higashino Keigo, which I read in French under the title La fleur de l´illusion [on a sunny Sunday afternoon, under my fig tree] and enjoyed both for its original, convoluted (and mostly convincing) plot and for the well-rendered interaction between the young protagonists. And also for having a few connections with my recent trip, from one protagonist studying nuclear physics at the University of Osaka to a visit to the back country of Katsuura. (The author himself graduated from Osaka Prefecture University with a Bachelor of Engineering degree.) Spoiler warning: the only annoying part of the plot was the resolution of the mystery via a secret society run by a few families of civil servants, which as always sounds to me like a rather cheap way out. But not enough to ruin the entire novel.

 

IMS workshop [day 2]

Posted in pictures, Statistics, Travel with tags , , , , , , , , , , , , on August 29, 2018 by xi'an

Here are the slides of my talk today on using Wasserstein distances as an intrinsic distance measure in ABC, as developed in our papers with Espen Bernton, Pierre Jacob, and Mathieu Gerber:

This morning, Gael Martin discussed the surprising aspects of ABC prediction, expanding upon her talk at ISBA, with several threads very much worth weaving in the ABC tapestry, one being that summary statistics need be used to increase the efficiency of the prediction, as well as more adapted measures of distance. Her talk also led me ponder about the myriad of possibilities available or not in the most generic of ABC predictions (which is not the framework of Gael’s talk). If we imagine a highly intractable setting, it may be that the marginal generation of a predicted value at time t+1 requires the generation of the entire past from time 1 till time t. Possibly because of a massive dependence on latent variables. And the absence of particle filters. if this makes any sense. Therefore, based on a generated parameter value θ it may be that the entire series needs be simulated to reach the last value in the series. Even when unnecessary this may be an alternative to conditioning upon the actual series. In this later case, comparing both predictions may act as a natural measure of distance since one prediction is a function or statistic of the actual data while the other is a function of the simulated data. Another direction I mused about is the use of (handy) auxiliary models, each producing a prediction as a new statistic, which could then be merged and weighted (or even selected) by a random forest procedure. Again, if the auxiliary models are relatively well-behaved, timewise, this would be quite straightforward to implement.

lecturer position in Data Centric Engineering and Statistics, Imperial College London

Posted in pictures, Statistics, Travel, University life with tags , , , , , , , , , , on April 2, 2018 by xi'an

My friend and Warwick colleague Mark Girolami sent me this announcement for a permanent Lecturer position at Imperial [College London], funded by his recent research chair by the Royal Academy of Engineering (congrats, Mark!). Deadline is April 13, so hurry up!!!

 

Bill Fitzgerald (1948-2014)

Posted in Books, Statistics, University life with tags , , , , on April 4, 2014 by xi'an

 

Just heard a very sad item of news: our colleague and friend Bill Fitzgerald, Head of Research in the Signal Processing Laboratory in the Department of Engineering at the University of Cambridge, Fellow of Christ’s College, co-founder and Chairman of Featurespace, and fanatic guitar player, passed away yesterday. He wrote one of the very first books on MCMC with Joseph Ó Ruanaidh, Numerical Bayesian Methods Applied to Signal Processing, in 1996. On a more personal level, he invited me to Cambridge for my first visit there  in 1998 and he thus was influential in introducing me to my friends Christophe Andrieu and Arnaud Doucet. Farewell, Bill!, and may the blessing of the rain be on you…