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stat.ML2026
Variational Smoothing and Inference for SDEs from Sparse Data with Dynamic Neural Flows
Yu Wang, Arnab Ganguly
Stochastic differential equations (SDEs) provide a flexible framework for modeling temporal dynamics in partially observed systems. A central task is to calibrate such models from…
stat.ML2025
Nonparametric learning of stochastic differential equations from sparse and noisy data
Arnab Ganguly, Riten Mitra, Jinpu Zhou
The paper proposes a systematic framework for building data-driven stochastic differential equation (SDE) models from sparse, noisy observations. Unlike traditional parametric appr…