My research interests are:
graphons, graph limits, random graphs, probability theory,
statistical learning, online learning, optimization, distributed algorithms
Publications & Preprints
Julien Weibel. Asymptotic properties of the maximum likelihood estimator for Hidden Markov Models indexed by binary trees.
Electronic Journal of Statistics 19 (2) 3370--3448, 2025.
[journal version;
preprint version: arXiv,
hal]
Julien Weibel, Pierre Gaillard, Wouter M. Koolen, Adrien Taylor.
Optimized projection-free algorithms for online learning: construction and worst-case analysis.
Preprint, 2025.
[arXiv,
hal]
Julien Weibel. Ergodic theorem for branching Markov
chains indexed by trees with arbitrary shape. Journal of
Applied Probability, Volume 62, Issue 3, pp. 1089--1104, 2025.
[journal version,
author accepted manuscript;
preprint version: arXiv,
hal]
Romain Abraham, Jean-François Delmas, Julien Weibel.
Probability-graphons: Limits of large dense weighted graphs.
Innovations in Graph Theory, vol. 2, pp. 25--117, 2025.
[journal version:
pdf,
journal website;
preprint version:
arXiv,
hal]
Julien Weibel. Graphons de probabilités,
limites de graphes pondérés aléatoires et
chaînes de Markov branchantes cachées. PhD
manuscript,
Université d'Orléans, 2024.
[PhD
manuscript,
or see on hal]
Achour Mostéfaoui, Matthieu Perrin, Julien Weibel.
Brief announcement: Randomized Consensus: Common Coins Are not the Holy Grail!.
ACM Symposium on Principles of Distributed
Computing (PODC 2024), 2024.
[Brief announcement,
hal]
Fatima-Ezzahra El Orche, Marcel Hollenstein, Sarah Houdaigoui, David Naccache, Daria Pchelina, Peter B Rønne, Peter y A Ryan, Julien Weibel, Robert Weil.
Taphonomical Security: (DNA) Information with a Foreseeable Lifespan.
Future of Information and Communication Conference (FICC), 2023.
[hal]