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math.OC2026
Pathwise Learning of Stochastic Dynamical Systems with Partial Observations
Nicole Tianjiao Yang
The reconstruction and inference of stochastic dynamical systems from data is a fundamental task in inverse problems and statistical learning. While surrogate modeling advances com…
math.OC2026
On the Convergence of Jacobian-Free Backpropagation for Optimal Control Problems with Implicit Hamiltonians
Eric Gelphman, Deepanshu Verma, Nicole Tianjiao Yang +2
Optimal feedback control with implicit Hamiltonians poses a fundamental challenge for learning-based value function methods due to the absence of closed-form optimal control laws.…
math.OC2025
End-to-End Training of High-Dimensional Optimal Control with Implicit Hamiltonians via Jacobian-Free Backpropagation
Eric Gelphman, Deepanshu Verma, Nicole Tianjiao Yang +2
Neural network approaches that parameterize value functions have succeeded in approximating high-dimensional optimal feedback controllers when the Hamiltonian admits explicit formu…