Strong Stochastic Flow Maps learn the strong solution map of additive-noise SDEs via a pathwise-convergent polynomial Brownian approximation, generalizing deterministic flow maps and enabling simulation-free training that outperforms prior weak-convergence stochastic methods on image generation and
Probability Theory and Stochastic Modelling, vol
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Derives weak convergence rates for combined CTRW approximations to time-fractional diffusions with unbounded coefficients via Feller semigroups and sensitivity analysis.
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Strong Stochastic Flow Maps
Strong Stochastic Flow Maps learn the strong solution map of additive-noise SDEs via a pathwise-convergent polynomial Brownian approximation, generalizing deterministic flow maps and enabling simulation-free training that outperforms prior weak-convergence stochastic methods on image generation and
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Convergence Rates of Continuous-Time Random Walks to Time-Fractional Diffusions with Unbounded Coefficients
Derives weak convergence rates for combined CTRW approximations to time-fractional diffusions with unbounded coefficients via Feller semigroups and sensitivity analysis.