On the 25 June edition, an editorial calling Europe to lead on free and open science, while boosting industrial consequences. (By the way, Japan just joined Horizon Europe! While the UK will rejoin Erasmus in 2027, under the headline “Brexit tore apart European science — now the research rifts are healing“, mentioning the financial and visa unsolved issues.) A news article continuing the investigation of how AI impacts or will impact mathematical research, with a FirstProof test evaluating AIs solving new, research-level, maths problems. (But missing Claude Mythos and Google’s Aletheia.) A “comment” from a Chinese academic that science needs humanities, at a time when universities in the UK are closing some humanities departments. And a discussion of the exceptional discovery of a whale necropolis, 7km deep, with fossil remains dating back to 5M years mixed with recent ones. Plus another exciting 10 page paper about genetic sleuthing on population changes at the collapse of the Roman empire, in the Danube-Isar and Rhein-Main areas of present-day Germany. (The attached picture representing posterior estimates of life expectancies of some individuals, obtained by MCMC.) In the Carreers section, a story from a geography researcher whose job offer was rescinded at the last moment, a scary thing that is alas not so rare.
Archive for whales
Nature tidbits
Posted in Books, Statistics, University life with tags AI, Brexit, Britain, Danube, fossils, Genetics, Germany, Horizon Europe, humanities, Isar, Japan, LLMs, Main, MCMC, Nature, Rhein, Roman Empire, whales on August 29, 2026 by xi'an…no el xe un pèse!!!
Posted in Kids, pictures, Travel with tags Austria, Austro-Hungary, Carlo Goldoni, Der Nord Wal, Friuli-Venezia, Gallo-Italic languages, German, Giacomo Casanova, Indo-European languages, Italy, Latin, maps, Old Norse, Republic of Venice, Romance language, tee-shirt, TNF, Venetan, Veneto, Venezia, whales on May 19, 2025 by xi'an
And here is the Venetan version of the nuova fanèla (tee-shirt), as suggested by my friend, co-author, and former PhD student Roberto Casarin, who hosted a fantastic ISBA last summer (and kindly looked after me while in ospedale!). Meaning this is not a fish! (If possibly a whale?!) For a better design Antoine and I had to give up the accent in pèse, much to my dismay. (End of the TNF series!)
…Der Nord Wal, but…
Posted in Books, Kids, pictures, Travel with tags Austria, Austro-Hungary, Der Nord Wal, French Revolution, German, Italy, maps, Napoléon Bonaparte, Napoleonic wars, narwhal, Old Norse, Republic of Venice, tee-shirt, TNF, Treaty of Campo Formio, Venetian, Venezia, whales, Yosemite on May 18, 2025 by xi'an
This new version in TNF memes came to life during my stay in Venezia last summer, as the fish or whale analogy struck me (after so many visits!). The German wording of the North whale afforded a proximity to the original brand without sharing a single word with said brand (and no connection with either the North Wall in Yosemite or the narwhal species, whose etymology link to the Old Norse for corpse-skinned whale). Antoine Luciano improved my early sketch of a three-part simplified map into the above (cutting out Santa Croce and inflating Giudecca) et voilà !
However, using a German motto for the map of Venezia may sound offensive to Venetian ears, reminding them of the 50 years of Austrian occupation—with both Napoléon Bonaparte and Napoléon III involved in the matter—, I consulted locals for another version and…
capture & maybe recapture
Posted in Books, pictures, Running, Statistics, University life with tags Arnason-Schwarz model, capture-recapture, Darroch model, Gibbs sampling, Grand Canal, misidentification, Parc de Sceaux, Sceaux, waterfowl, whales on September 5, 2023 by xi'an
I read population size estimation with capture-recapture in presence of individual misidentification and low recapture arXived by Rémy Fraysse and coauthors on my flight back from Saigon. The setup is one of a capture-recapture experience where potential misidentification (of a recapture individual labelled as new) may occur due to visual identification errors as, e.g., in whale studies. Trying to handle the issue, Yoshizaki et al. (2011) proposed adding one layer to the temporal Darroch model M[t] via a probability α of creating a “ghost” (by failing to recognise a formerly observed individual). When representing the experiment as a partly observed Markov process (as in Dupuis, 1995), this addition brings another completely latent process for misidentification. Completely in the sense that a misidentification is never observed (while a proper identification is). This means there is an issue with identifiability between failing to capture and misidentification, as a new individual may be captured for the first time or misidentified on that round.
Processing this model (i.e., producing a simulation algorithm of the posterior) can be done formally by a Gibbs completion (as in Dupuis, 1995) but this may prove a non-irreducible scheme (Schofer & Bonner, 2015), a problem solved by considering instead Metropolis-Hastings steps. The current paper is an extension of the above to the multiple states Arnason-Schwarz model with no theoretical convergence issue, besides running a large sized completion. It is mostly a simulation experiment with a comparison on different priors on the misspecification rate, some highly informative, others not, with a frequentist assessment of coverage. Given the identifiability issue mentioned above, this is not particularly helpful since it simply exhibits the fact that with the right priors the parameter values are unbiasedly estimated, while a low recapture plus high misidentification setting makes estimation more difficult.
Ocean’s four!
Posted in Books, pictures, Statistics, University life with tags #ERCSyG, Bayesian Analysis, Brussels, data privacy, data processing, decentralized networks, decision-making agents, ERC, European Research Council, machine learning, multi-agent decision theory, murmuration, Ocean, probabilistic machine learning, starlings, statistical inference, stochastic optimization, The Ocean at the End of the Lane, uncertainty quantification, whales on October 25, 2022 by xi'an
Fantastic news! The ERC-Synergy¹ proposal we submitted last year with Michael Jordan, Éric Moulines, and Gareth Roberts has been selected by the ERC (which explains for the trips to Brussels last month). Its acronym is OCEAN [hence the whale pictured by a murmuration of starlings!], which stands for On intelligenCE And Networks: Mathematical and Algorithmic Foundations for Multi-Agent Decision-Making. Here is the abstract, which will presumably turn public today along with the official announcement from the ERC:
Until recently, most of the major advances in machine learning and decision making have focused on a centralized paradigm in which data are aggregated at a central location to train models and/or decide on actions. This paradigm faces serious flaws in many real-world cases. In particular, centralized learning risks exposing user privacy, makes inefficient use of communication resources, creates data processing bottlenecks, and may lead to concentration of economic and political power. It thus appears most timely to develop the theory and practice of a new form of machine learning that targets heterogeneous, massively decentralized networks, involving self-interested agents who expect to receive value (or rewards, incentive) for their participation in data exchanges.
OCEAN will develop statistical and algorithmic foundations for systems involving multiple incentive-driven learning and decision-making agents, including uncertainty quantification at the agent’s level. OCEAN will study the interaction of learning with market constraints (scarcity, fairness), connecting adaptive microeconomics and market-aware machine learning.
OCEAN builds on a decade of joint advances in stochastic optimization, probabilistic machine learning, statistical inference, Bayesian assessment of uncertainty, computation, game theory, and information science, with PIs having complementary and internationally recognized skills in these domains. OCEAN will shed a new light on the value and handling data in a competitive, potentially antagonistic, multi-agent environment, and develop new theories and methods to address these pressing challenges. OCEAN requires a fundamental departure from standard approaches and leads to major scientific interdisciplinary endeavors that will transform statistical learning in the long term while opening up exciting and novel areas of research.
Since the ERC support in this grant mostly goes to PhD and postdoctoral positions, watch out for calls in the coming months or contact us at any time.
