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stat.ML2026
Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation
J. H. Ramirez-Gonzalez
We consider the estimation of drift, diffusion, and noise covariance from discrete observations of stochastic differential equations driven by Gaussian processes. For a fixed obser…
stat.ML2025
Neural Networks for Tamed Milstein Approximation of SDEs with Additive Symmetric Jump Noise Driven by a Poisson Random Measure
Jose-Hermenegildo Ramirez-Gonzalez, Ying Sun
This work aims to estimate the drift and diffusion functions in stochastic differential equations (SDEs) driven by a particular class of Lévy processes with finite jump intensity,…