scientific article; zbMATH DE number 7370549
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Publication:4998909
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Publication date: 9 July 2021
Full work available at URL: https://arxiv.org/abs/1910.04832
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inverse problemsMonte Carlo samplinginteracting particle systemsnonparametric statisticsregularized least squares
Related Items (15)
Parameter calibration with stochastic gradient descent for interacting particle systems driven by neural networks ⋮ ISALT: inference-based schemes adaptive to large time-stepping for locally Lipschitz ergodic systems ⋮ Numerical Identification of Nonlocal Potentials in Aggregation ⋮ Statistical inference for mean-field queueing models ⋮ Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories ⋮ Learning mean-field equations from particle data using WSINDy ⋮ Learning theory for inferring interaction kernels in second-order interacting agent systems ⋮ Reproducing kernel Hilbert spaces in the mean field limit ⋮ Online parameter estimation for the McKean-Vlasov stochastic differential equation ⋮ On the coercivity condition in the learning of interacting particle systems ⋮ Identifiability of interaction kernels in mean-field equations of interacting particles ⋮ Weak SINDy: Galerkin-Based Data-Driven Model Selection ⋮ The LAN property for McKean-Vlasov models in a mean-field regime ⋮ Learning stochastic dynamics with statistics-informed neural network ⋮ Learning Interaction Kernels in Mean-Field Equations of First-Order Systems of Interacting Particles
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