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An extension of the stochastic sewing lemma and applications to fractional stochastic calculus

Toyomu Matsuda

We give an extension of Le's stochastic sewing lemma. The stochastic sewing lemma proves convergence in

L_m

of Riemann type sums

\sum _{[s,t] \in \pi } A_{s,t}

for an adapted two-parameter stochastic process A, under certain conditions on the moments o ...

Cambridge Univ Press2024

Corrélation (statistiques)

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An extension of the stochastic sewing lemma and applications to fractional stochastic calculus

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise

Differential Entropy of the Conditional Expectation under Gaussian Noise

A quantum algorithm for the direct estimation of the steady state of open quantum systems

Stochastic approximation methods for PDE constrained optimal control problems with uncertain parameters

Deterministic Algorithms for Submodular Maximization Problems

Spontaneous symmetry breaking in a quadratically driven nonlinear photonic lattice

Robust Data-Driven Dynamic Programming

Propagation Models for Biochemical Reaction Networks

An extension of the stochastic sewing lemma and applications to fractional stochastic calculus

Stochastic approximation methods for PDE constrained optimal control problems with uncertain parameters

Differential Entropy of the Conditional Expectation Under Additive Gaussian Noise

Quantifying uncertain system outputs via the multi-level Monte Carlo method --- distribution and robustness measures

A quantum algorithm for the direct estimation of the steady state of open quantum systems

Spontaneous symmetry breaking in a quadratically driven nonlinear photonic lattice

Robust Data-Driven Dynamic Programming

Differential Entropy of the Conditional Expectation under Gaussian Noise

Propagation Models for Biochemical Reaction Networks

Deterministic Algorithms for Submodular Maximization Problems