congrats, Dr. Clarté!

Grégoire Clarté, whom I co-supervised with Robin Ryder, successfully defended his PhD thesis last Wednesday! On sign language classification, ABC-Gibbs and collective non-linear MCMC. Congrats to the now Dr.Clarté for this achievement and all the best for his coming Nordic adventure, as he is starting a postdoc at the University of Helsinki, with Aki Vehtari and others. It was quite fun to work with Grégoire along these years. And discussing on an unlimited number of unrelated topics, incl. fantasy books, teas, cooking and the role of conferences and travel in academic life! The defence itself proved a challenge as four members of the jury, incl. myself, were “present remotely” and frequently interrupted him for gaps in the Teams transmission, which nonetheless broadcasted perfectly the honks of the permanent traffic jam in Porte Dauphine… (And alas could not share a celebratory cup with him!)

NCE, VAEs, GANs & even ABC…

As I was preparing my (new) lectures for a PhD short course “at” Warwick (meaning on Teams!), I read a few surveys and other papers on all these acronyms. It included the massive Guttmann and Hyvärinen 2012 NCE JMLR paper,  Goodfellow’s NIPS 2016 tutorial on GANs, and  Kingma and Welling 2019 introduction to VAEs. Which I found a wee bit on the light side, maybe missing the fundamentals of the notion… As well as the pretty helpful 2019 survey on normalising flows by Papamakarios et al., although missing on the (statistical) density estimation side.  And also a nice (2017) survey of GANs by Shakir Mohamed and Balaji Lakshminarayanan with a somewhat statistical spirit, even though convergence issues are not again not covered. But misspecification is there. And the many connections between ABC and GANs, if definitely missing on the uncertainty aspects. While Deep Learning by Goodfellow, Bengio and Courville adresses both the normalising constant (or partition function) and GANs, it was somehow not deep enough (!) to use for the course, offering only a few pages on NCE, VAEs and GANs. (And also missing on the statistical references addressing the issue, incl. [or excl.]  Geyer, 1994.) Overall, the infinite variations offered on GANs leave me uncertain about their statistical relevance, as it is unclear how good the regularisation therein is for handling overfitting and consistent estimation. (And if I spot another decomposition of the Kullback-Leibler divergence, I may start crying…)

platform fatigue

With the myriad of platforms used to counteract the absence of most direct interactions at work, I start to suffer from platform fatigue, constantly switching to a different interface and wasting a lot of time on retrieving links from old emails and reentering passwords… Even a single platform like Teams requires permanent juggling between Dauphine and Warwick (obviously linked with Microsoft constraints), plus repeated updates that clash more often than enough with Firefox. Not to mention collaborative systems like Overleaf, Wikimath, Git, and others. Same thing for regular Zoom meetings which fail to reopen from one week to the next. And calendars that cannot keep track of everything or even anything! The only interface that keeps working (for me) across accounts is my Thunderbird email interface, except for the sharp increase in the email volume (and the fact that many now bypass emails for chats on Teams, Slack, and another myriad of platforms).

dire new semester, indeed…