Image de couverture de livre

A new local time-decoupled squared Wasserstein-2 method for training stochastic neural networks to reconstruct uncertain parameters in dynamical systems

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Xia, Mingtao, Shen, Qijing, Maini, Philip, Gaffney, Eamonn, Mogilner, Alex
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning Probability 60G05, 60H10
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

A local squared Wasserstein-2 method for efficient reconstruction of models with uncertainty
par: Xia, Mingtao, et autres
Publié: (2024)

Efficient reconstruction of multidimensional random field models with heterogeneous data using stochastic neural networks
par: Xia, Mingtao, et autres
Publié: (2025)

A generalized Wasserstein-2 distance approach for efficient reconstruction of random field models using stochastic neural networks
par: Xia, Mingtao, et autres
Publié: (2025)

An efficient Wasserstein-distance approach for reconstructing jump-diffusion processes using parameterized neural networks
par: Xia, Mingtao, et autres
Publié: (2024)

Squared Wasserstein-2 Distance for Efficient Reconstruction of Stochastic Differential Equations
par: Xia, Mingtao, et autres
Publié: (2024)

On local large deviations for decoupled random walks
par: Buraczewski, Dariusz, et autres
Publié: (2025)

2BSDE with uncertain horizon and application to stochastic control in erratic environments
par: Gennaro, Alberto, et autres
Publié: (2025)

Limit theorems for anisotropic functionals of stationary Gaussian fields with Gneiting covariance function
par: Leonenko, Nikolai, et autres
Publié: (2026)

Sharp supremum and Hölder bounds for stochastic integrals indexed by a parameter
par: Cox, Sonja, et autres
Publié: (2024)

Almost sure central limit theorems via chaos expansions and related results
par: Maini, Leonardo, et autres
Publié: (2025)

Stabilization of stochastic networks in Markovian environment
par: Kaiser, Robin, et autres
Publié: (2026)

Mean field analysis of stochastic networks with reservation
par: Fricker, Christine, et autres
Publié: (2022)

Integrability properties and stochastic McKean-Vlasov dynamics with singular Lennard-Jones drift: a mesoscale regularization
par: Greco, Ernesto M., et autres
Publié: (2026)

Splitting methods for stochastic Hodgkin-Huxley type systems and a localized fundamental mean-square convergence theorem
par: Étoré, Pierre, et autres
Publié: (2026)

Limit theorems for sticky SDEs with local times and applications to stochastic homogenization
par: Aryasova, Olga, et autres
Publié: (2025)

Diffusion Processes on $p$-Wasserstein Space over Banach Space
par: Ren, Panpan, et autres
Publié: (2024)

Well-posedness of stochastic reacting particle systems with non-local and Lennard-Jones interactions
par: Morale, Daniela, et autres
Publié: (2026)

Regulating stochastic clocks
par: Fei, Zhe, et autres
Publié: (2022)

Convergence rates for the $p$-Wasserstein distance of the empirical measures of an ergodic Markov process
par: Schilling, René L., et autres
Publié: (2025)

Mean convergence rates for Gaussian-smoothed Wasserstein distances and classical Wasserstein distances
par: Cosso, Andrea, et autres
Publié: (2025)

Strong local nondeterminism for stochastic time-fractional slow and fast diffusion equations
par: Chen, Le, et autres
Publié: (2026)

A new approach to stochastic McKean-Vlasov limits with low-regularity coefficients
par: Crowell, Robert Alexander
Publié: (2025)

Interacting stochastic processes on sparse random graphs
par: Ramanan, Kavita
Publié: (2023)

Cover times with stochastic resetting
par: Linn, Samantha, et autres
Publié: (2024)

Local linearization for estimating the diffusion parameter of nonlinear stochastic wave equations with spatially correlated noise
par: Liu, Guoping, et autres
Publié: (2025)

Malliavin differentiability for the excursion measure of a Gaussian field
par: Maini, Leonardo
Publié: (2025)

Large deviation principle for stochastic differential equations driven by stochastic integrals
par: Takano, Ryoji
Publié: (2024)

Tightness and weak convergence in the topology of local uniform convergence for stochastic processes in the dual of a nuclear space
par: Fonseca-Mora, C. A.
Publié: (2023)

Wasserstein contraction for the stochastic Morris-Lecar neuron model
par: Herda, Maxime, et autres
Publié: (2023)

Convergence rate of the occupation measure of classes of ergodic processes toward their invariant distribution in mean Wasserstein distance
par: Pagès, Gilles, et autres
Publié: (2026)

A transfer principle for computing the adapted Wasserstein distance between stochastic processes
par: Jiang, Yifan, et autres
Publié: (2025)

Large deviation principles and functional limit theorems in the deep limit of wide random neural networks
par: Di Lillo, Simmaco, et autres
Publié: (2026)

Walsh Spider Diffusions as Time Changed Multi-parameter Processes
par: Bayraktar, Erhan, et autres
Publié: (2022)

Stochastic intrinsic gradient flows on the Wasserstein space
par: Ren, Panpan, et autres
Publié: (2025)

Sticky-threshold diffusions, local time approximation and parameter estimation
par: Anagnostakis, Alexis, et autres
Publié: (2024)

Convergence of local times of stochastic processes associated with resistance forms
par: Noda, Ryoichiro
Publié: (2023)

Phase Transitions in the Fluctuations of Functionals of Random Neural Networks
par: Di Lillo, Simmaco, et autres
Publié: (2026)

Some new concentration inequalities for the Itô stochastic integral
par: Dung, Nguyen Tien
Publié: (2023)

Self-intersection local times for Volterra Gaussian processes in stochastic flows with interaction
par: Izyumtseva, Olga, et autres
Publié: (2026)

Dual process in the two-parameter Poisson-Dirichlet diffusion
par: Griffiths, Robert C., et autres
Publié: (2021)