9 citations · 17 across the 12 of their papers we have counts for
13 papers
Bayesian statistical inverse problems for a coupled Fokker-Planck-Darcy system
Grigorios A. Pavliotis, Andrew M. Stuart, Andrea Zanoni
We study the nonparametric statistical inverse problem of recovering the space-dependent permittivity in a coupled Fokker-Planck-Darcy system from discrete, noisy observations of t…
A Fourier-based inference method for learning interaction kernels in particle systems
Grigorios A. Pavliotis, Andrea Zanoni
We consider the problem of inferring the interaction kernel of stochastic interacting particle systems from observations of a single particle. We adopt a semi-parametric approach a…
Linearization of ergodic McKean SDEs and applications
Grigorios A. Pavliotis, Andrea Zanoni
In this article, we consider McKean stochastic differential equations, as well as their corresponding McKean-Vlasov partial differential equations, which admit a unique stationary…
Filtered data based estimators for stochastic processes driven by colored noise
Grigorios A. Pavliotis, Sebastian Reich, Andrea Zanoni
We consider the problem of estimating unknown parameters in stochastic differential equations driven by colored noise, which we model as a sequence of Gaussian stationary processes…
A method of moments estimator for interacting particle systems and their mean field limit
Grigorios A. Pavliotis, Andrea Zanoni
We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction and diffusion functions from the path of one singl…
Homogenization results for the generator of multiscale Langevin dynamics in weighted Sobolev spaces
Andrea Zanoni
We study the homogenization of the Poisson equation with reaction term and of the eigenvalue problem associated to the generator of multiscale Langevin dynamics. Our analysis exten…
Eigenfunction martingale estimators for interacting particle systems and their mean field limit
Grigorios A. Pavliotis, Andrea Zanoni
We study the problem of parameter estimation for large exchangeable interacting particle systems when a sample of discrete observations from a single particle is known. We propose…
Robust Estimation of Effective Diffusions from Multiscale Data
Giacomo Garegnani, Andrea Zanoni
We present a novel methodology based on filtered data and moving averages for estimating effective dynamics from observations of multiscale systems. We show in a semi-parametric fr…
Eigenfunction martingale estimating functions and filtered data for drift estimation of discretely observed multiscale diffusions
Assyr Abdulle, Grigorios A. Pavliotis, Andrea Zanoni
We propose a novel method for drift estimation of multiscale diffusion processes when a sequence of discrete observations is given. For the Langevin dynamics in a two-scale potenti…
Minimax Classification with 0-1 Loss and Performance Guarantees
Santiago Mazuelas, Andrea Zanoni, Aritz Perez
Supervised classification techniques use training samples to find classification rules with small expected 0-1 loss. Conventional methods achieve efficient learning and out-of-samp…
Drift Estimation of Multiscale Diffusions Based on Filtered Data
Assyr Abdulle, Giacomo Garegnani, Grigorios A. Pavliotis +2
We study the problem of drift estimation for two-scale continuous time series. We set ourselves in the framework of overdamped Langevin equations, for which a single-scale surrogat…
Ensemble Kalman filter for multiscale inverse problems
Assyr Abdulle, Giacomo Garegnani, Andrea Zanoni
We present a novel algorithm based on the ensemble Kalman filter to solve inverse problems involving multiscale elliptic partial differential equations. Our method is based on nume…
Supervised classification via minimax probabilistic transformations
Santiago Mazuelas, Andrea Zanoni, Aritz Perez
Conventional techniques for supervised classification constrain the classification rules considered and use surrogate losses for classification 0-1 loss. Favored families of classi…