Category: pictures

Nature tea[dbits]

A very special issue of Nature (7 February 2019, vol. 556, no. 7742). With an outlook section on tea, plus a few research papers (and ads) on my principal beverage. News about the REF, Elsevier’s and Huawei’s woes with the University of California, the dangerous weakening of Title IX by the Trump administration, and a […]

off to Cambodia

Today, I am off to Cambodia for a small conference on Data Science and Finance, mostly finance, actually!, put together by a group of French and Cambodian colleagues and taking place in Siem Reap near the fabulous temples of Angkor Wat. Expect pictures in the following posts if I manage to stand the heat and […]

call for sessions and labs at Bay2sC0mp²⁰

A call to all potential participants to the incoming BayesComp 2020 conference at the University of Florida in Gainesville, Florida, 7-10 January 2020, to submit proposals [to me] for contributed sessions on everything computational or training labs [to David Rossell] on a specific language or software. The deadline is April 1 and the sessions will […]

and it only gets worse…

” A recent survey by Bankrate.com found that just 40% of US households have enough money to cover a $1,000 in emergency expenses.” The Guardian, Feb 2, 2019 ““Until we heard those cheers coming from Albany, we thought states were moving beyond such barbaric practices.” Mr. Pence offered his argument as a litmus test of […]

Bayesian intelligence in Warwick

This is an announcement for an exciting CRiSM Day in Warwick on 20 March 2019: with speakers 10:00-11:00 Xiao-Li Meng (Harvard): “Artificial Bayesian Monte Carlo Integration: A Practical Resolution to the Bayesian (Normalizing Constant) Paradox” 11:00-12:00 Julien Stoehr (Dauphine): “Gibbs sampling and ABC” 14:00-15:00 Arthur Ulysse Jacot-Guillarmod (École Polytechnique Fedérale de Lausanne): “Neural Tangent Kernel: […]

Bayesian intelligence in Warwick

This is an announcement for an exciting CRiSM Day in Warwick on 20 March 2019: with speakers 10:00-11:00 Xiao-Li Meng (Harvard): “Artificial Bayesian Monte Carlo Integration: A Practical Resolution to the Bayesian (Normalizing Constant) Paradox” 11:00-12:00 Julien Stoehr (Dauphine): “Gibbs sampling and ABC” 14:00-15:00 Arthur Ulysse Jacot-Guillarmod (École Polytechnique Fedérale de Lausanne): “Neural Tangent Kernel: […]

O’Bayes 19: registration and travel support

An update about the O’Bayes 19 conference next June-July:  the early registration period has now opened. And there should be funds for supporting early-career researchers, thanks to Google and CNRS sponsorships, as detailed below: Early-career researchers less than four years from PhD, are invited to apply for early-career scholarships. If you are a graduate student, […]

a pen for ABC

Among the flury of papers arXived around the ICML 2019 deadline, I read on my way back from Oxford a paper by Wiqvist et al. on learning summary statistics for ABC by neural nets. Pointing out at another recent paper by Jiang et al. (2017, Statistica Sinica) which constructed a neural network for predicting each […]

Fisher’s lost information

After a post on X validated and a good discussion at work, I came to the conclusion [after many years of sweeping the puzzle under the carpet] that the (a?) Fisher information obtained for the Uniform distribution U(0,θ) as θ⁻¹ is meaningless. Indeed, there are many arguments: The lack of derivability of the indicator function […]

revisiting marginalisation paradoxes [Bayesian reads #1]

As a reading suggestion for my (last) OxWaSP Bayesian course at Oxford, I included the classic 1973 Marginalisation paradoxes by Phil Dawid, Mervyn Stone [whom I met when visiting UCL in 1992 since he was sharing an office with my friend Costas Goutis], and Jim Zidek. Paper that also appears in my (recent) slides as […]

information maximising neural networks summaries

After missing the blood moon eclipse last night, I had a meeting today at the Paris observatory (IAP), where we discussed an ABC proposal made by Tom Charnock, Guilhem Lavaux, and Benjamin Wandelt from this institute. “We introduce a simulation-based machine learning technique that trains artificial neural networks to find non-linear functionals of data that […]

O’Bayes 2019: poster deadline extension

For potential participants to the ISBA O’Bayes 2019 conference in Warwick next June 28 – July 02, that is, almost everyone except the participants who have already submitted!, this post is to announce that the deadline for poster submission has just been extended till March 15, to account for BNP 12 potential participants having not […]

plenary speakers for BayesComp 20[20]

As a co-chair of the incoming ISBA BayesComp 2020 in Gainesville, Florida, 7-10 January 2020. I am very glad to broadcast that the four plenary speakers for the conference are David Blei (Columbia U) Paul Fearnhead (U Lancaster) Emily Fox (U Washington) Max Welling (U Amsterdam) There will soon be a call for contributed sessions, […]

risk-adverse Bayes estimators

An interesting paper came out on arXiv in early December, written by Michael Brand from Monash. It is about risk-adverse Bayes estimators, which are defined as avoiding the use of loss functions (although why avoiding loss functions is not made very clear in the paper). Close to MAP estimates, they bypass the dependence of said […]