Estimation of Self-Exciting Point Processes from Time-Censored Data
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Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...
We study the problem of learning unknown parameters of stochastic dynamical models from data. Often, these models are high dimensional and contain several scales and complex structures. One is then interested in obtaining a reduced, coarse-grained descript ...
For estimating parameters of discrete choice models, observations corresponding to the models are required. In the context of route choice models, we need the information of paths, which are sequences of links and connect between the origin-destination pa ...
The proliferation of (low-cost) sensors provokes new challenges in data fusion. This is related to the correctness of stochastic characterization that is a prerequisite for optimal estimation of parameters from redundant observations. Different (statistica ...
This paper introduces a new algorithm for consensus optimization in a multi-agent network, where all agents collaboratively find a minimizer for the sum of their private functions. All decentralized algorithms rely on communications between adjacent nodes. ...
We propose a cheaper version of a posteriori error estimator from Gorynina et al. (Namer. Anal. (2017)) for the linear second-order wave equation discretized by the Newmark scheme in time and by the finite element method in space. The new estimator preserv ...
xtreme value analysis is concerned with the modelling of extreme events such as floods and heatwaves, which can have large impacts. Statistical modelling can be useful to better assess risks even if, due to scarcity of measurements, there is inherently ver ...
Aims. We investigate the contribution of shot-noise and sample variance to uncertainties in the cosmological parameter constraints inferred from cluster number counts, in the context of the Euclid survey. Methods. By analysing 1000 Euclid-like light cones, ...
The paper addresses the problem of designing distributed observers for discrete linear time-invariant (LTI) systems with distributed sensor nodes subjected to bounded measurement noise. A solution is proposed in terms of a distributed LTI Luenberger observ ...
The main topics of this thesis are distributed estimation and cooperative path-following in the presence of communication constraints, with applications to autonomous marine vehicles. To this end, we study algorithms that take explicitly into account the c ...