144 citations
- Centre de Recherche en Économie et StatistiqueFR78 papers
- Center for Responsible TravelUS49 papers
- ENSAE ParisFR23 papers
- The University of TokyoJP18 papers
- Science and Technology Corporation (United States)US15 papers
- Centre de Recherche en Sciences et Technologies de l'Information et de la CommunicationFR12 papers
- École Nationale de la Statistique et de l'Analyse de l'InformationFR10 papers
- Centre de Recherche en Mathématiques de la DécisionFR8 papers
- Laboratoire de Probabilités et Modèles AléatoiresFR8 papers
- Université Paris Dauphine-PSLFR6 papers
- Tohoku UniversityJP5 papers
- Tokyo University of ScienceJP5 papers
7 papers · 1 filter
Cyber risk modeling using a two-phase Hawkes process with external excitation
Alexandre Boumezoued, Yousra Cherkaoui, Caroline Hillairet
With the growing digital transformation of the worldwide economy, cyber risk has become a major issue. As 1 % of the world's GDP (around $1,000 billion) is allegedly lost to cyberc…
Two New Integer Sequences Related to Crossroads and Catalan Numbers
Julien Rouyer, Alain Ninet
The lonely singles sequence represents the number of noncrossing partitions of the finite set {1,. .. , n} in which no pair of singletons {i} and {j} can be merged into the pair {i…
Logarithmic Mathematical Morphology: Theory and applications
Guillaume Noyel
In Mathematical Morphology for grey-level functions, an image is analysed by another image named the structuring function. This structuring function is translated over the image do…
Deformation Cohomology of Lie-Yamaguti algebras and Free Lie-Yamaguti algebras
Saikat Goswami
Infinitesimal deformation theory of Lie-Yamaguti algebras was introduced by Tao Zhang and Juan Li . We extend their theory to develop formal one-parameter deformation theory of Lie…
Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
Elen Vardanyan, Sona Hunanyan, Tigran Galstyan +2
This paper explores the problem of generative modeling, aiming to simulate diverse examples from an unknown distribution based on observed examples. While recent studies have focus…
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization
Clément Bénard, Brian Staber, Sébastien Da Veiga
Stein thinning is a promising algorithm proposed by (Riabiz et al., 2022) for post-processing outputs of Markov chain Monte Carlo (MCMC). The main principle is to greedily minimize…