Phi, Tien Cuong Muzy, Alexandre Reynaud-Bouret, Patricia
Published in
SN Computer Science

Event-scheduling algorithms can compute in continuous time the next occurrence of points (as events) of a counting process based on their current conditional intensity. In particular, event-scheduling algorithms can be adapted to perform the simulation of finite neuronal networks activity. These algorithms are based on Ogata’s thinning strategy (Og...

Selosse, Margot Jacques, Julien Biernacki, Christophe

Over decades, a lot of studies have shown the importance of clustering to emphasize groups of observations. More recently, due to the emergence of high-dimensional datasets with a huge number of features, co-clustering techniques have emerged and proposed several methods for simultaneously producing groups of observations and features. By synthesiz...

Delavoie, Franck Soldan, Vanessa Rinaldi, Dana Dauxois, Jean-Yves Gleizes, Pierre-Emmanuel
Published in
Nature Communications

Large protein complexes and ribonucleoprotein particles (RNPs) such as pre-ribosomes are transported from the nucleus to the cytoplasm through the nuclear pore complex (NPC). Here the authors use ultrafast freezing and electron tomography to catch snapshots of native RNPs crossing the NPC and estimate their transit time using a probabilistic model....

Klyapovskiy, Sergey You, Shi Michiorri, Andrea Kariniotakis, Georges Bindner, Henrik

Distributed energy resources (DER) and new types of consumer equipment create many challenges for distribution system operators (DSOs). Power congestions that can potentially be created during normal or contingency situations will lead to increased investments into grid reinforcement. An alternative solution is to use the flexibility provided by th...

Neverov, Cyprien Khnifass, Chihab Beye, Papa Sutton-Charani, Nicolas Imoussaten, Abdelhak Fagart, W Blot, M. Dupeyron, A.

Cet article concerne la modélisation de données incertaines à partir de mesures répétées mais non-reproductibles. Différentes approches issues des théories modernes de l'incertain sont considérées. Plus précisément, l'article s'intéresse à diverses extensions de tests statistiques non-paramétriques aux données incertaines. Dans ce travail prélimina...

Barraquand, Frédéric Picoche, Coralie Detto, Matteo Hartig, Florian

Identifying directed interactions between species from time series of their population densities has many uses in ecology. This key statistical task is equivalent to causal time series inference, which connects to the Granger causality (GC) concept: $x$ causes $y$ if $x$ improves the prediction of $y$ in a dynamic model. However, the entangled natu...

Nguyen, Hien Chamroukhi, Faicel Forbes, Florence

Mixture of experts (MoE) models are a class of artificial neural networks that can be used for functional approximation and probabilistic modeling. An important class of MoE models is the class of mixture of linear experts (MoLE) models, where the expert functions map to real topological output spaces. Recently, Gaussian gated MoLE models have beco...

Abeille, Marc Lazaric, Alessandro

We derive an alternative proof for the regret of Thompson sampling (\ts) in the stochastic linear bandit setting. While we obtain a regret bound of order $\widetilde{O}(d^{3/2}\sqrt{T})$ as in previous results, the proof sheds new light on the functioning of the \ts. We leverage on the structure of the problem to show how the regret is related to t...

Le Gratiet, Loic

The response spectrum method is commonly used to design multi-degree-of-freedom structures subject to random vibrations. However, the common direction combination rules (SRSS, Newmark 30-100-100, Newmark 40-100-100) consider uncorrelated excitation components. Theoretically, it is always possible to rotate the directions in order to obtain principa...

Leipus, Remigijus Philippe, Anne Pilipauskaite, Vytaute Surgailis, Donatas

The present paper obtains a complete description of the limit distributions of sample covariances in N × n panel data when N and n jointly increase, possibly at different rate. The panel is formed by N independent samples of length n from random-coefficient AR(1) process with the tail distribution function of the random coefficient regularly varyin...