3 papers
stat.ML2026
Identifying parameter couplings and uncertainties of mixed-noise stochastic systems via full-covariance Gaussian mixture network
Xiaolong Wang, Xiangwen Hao, Jing Feng +2
Parameter identification of stochastic dynamical systems driven by mixed noises is challenging due to intractable likelihood functions. We propose PENN-GMD, a parameter estimation…
physics.comp-ph2026
A deep learning framework for jointly solving transient Fokker-Planck equations with arbitrary parameters and initial distributions
Xiaolong Wang, Jing Feng, Qi Liu +3
Efficiently solving the Fokker-Planck equation (FPE) is central to analyzing complex parameterized stochastic systems. However, current numerical methods lack parallel computation…
math.PR2025
Computable Bounds on the Solution to Poisson's Equation for General Harris Chains
Peter W. Glynn, Na Lin, Yuanyuan Liu
Poisson's equation is fundamental to the study of Markov chains, and arises in connection with martingale representations and central limit theorems for additive functionals, pertu…