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Publications associées (28)

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Fabio Nobile, Sebastian Krumscheid, Matthieu Claude Martin

We consider the numerical approximation of an optimal control problem for an elliptic Partial Differential Equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes the expected ...

2021

A parametrized Kalman filter for fast track fitting at LHCb

Michel De Cian

We present an alternative implementation of the Kalman filter employed for track fitting within the LHCb experiment. It uses simple parametrizations for the extrapolation of particle trajectories in the field of the LHCb dipole magnet and for the effects o ...

2021

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Lubna Dada

Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, ...

Copernicus Publications2021

Computational approaches to decode grasping force and velocity level in upper-limb amputee from intraneural peripheral signals

Silvestro Micera, Ivo Strauss, Giacomo Valle

Objective. Recent results have shown the potentials of neural interfaces to provide sensory feedback to subjects with limb amputation increasing prosthesis usability. However, their advantages for decoding motor control signals over current methods based o ...

IOP Publishing Ltd2021

Monte Carlo Estimators for Differential Light Transport

Wenzel Alban Jakob, Tizian Lucien Zeltner, Sébastien Nicolas Speierer

Physically based differentiable rendering algorithms propagate derivatives through realistic light transport simulations and have applications in diverse areas including inverse reconstruction and machine learning. Recent progress has led to unbiased metho ...

ASSOC COMPUTING MACHINERY2021

Similarity conditions and cube model tests of snow drift and precipitation preferential deposition patterns

Michael Lehning

We explore the process of modeling aeolian snow transport around buildings by proposing a set of similarity requirements on simulating a single snow fall event with drifting. The similarity criteria are used to guide our wind tunnel tests from the particle ...

ELSEVIER2021

Nonlinear kinetic simulation study of the ion-ion streaming instability in single- and multi-ion species plasmas

Stephan Brunner

The nonlinear evolution of the ion-ion streaming instability (IISI) is studied using numerical techniques novel to this problem that afford direct insight into the evolution of the particle distributions of each species. During the linear phase of the inst ...

2021

Constrained expectation-maximization algorithm for stochastic inertial error modeling: study of feasibility

Jan Skaloud, Stéphane Guerrier, Yannick Stebler

Stochastic modeling is a challenging task for low-cost sensors whose errors can have complex spectral structures. This makes the tuning process of the INS/GNSS Kalman filter often sensitive and difficult. For example, first-order Gauss–Markov processes are ...

IOP Publishing2011