7 papers
Geometric Identification in Predict-Then-Optimize Learning
Jiaxiao Xu, Changhong Mou, Keji Liu +2
Decision-focused surrogates can recover downstream decisions without identifying the quotient report. We characterize the equality set of the convex Smart Predict-then-Optimize sur…
Stochastic Physics-Constrained Operator Inference for Complex Systems
Changhong Mou
Quadratically nonlinear systems driven by additive noise arise throughout science and engineering, both as stochastic dynamical systems in their own right and as reduced-order mode…
Finance-Informed Operator Learning for Option Pricing with Quantum-Compatible Realizations
Jiarui Feng, Bingyang Hu, Yu Jiang +3
Pricing European options under local volatility requires repeatedly solving a PDE whose coefficients change with recalibration, while practitioners need both prices and sensitiviti…
ATLAS-NN: Adaptive Transfer Learnable Symplectic-aware Neural Network for Long-Time Hamiltonian Dynamics
Changhong Mou, Dinghua Xu, Xiyue Zuo +2
Modeling Hamiltonian systems over long temporal intervals remains a significant challenge due to intrinsic multiscale structures and rapid nonlinear transitions. While Hamiltonian…
PACE-FNO: Physics-Aligned Canonical Equivariance for Fourier Neural Operators
Jiaxiao Xu, Changhong Mou, Yeyu Zhang +1
Neural operators are often tested on states that differ physically from training data. A distinct failure occurs when the physical dynamics are unchanged but the observed coordinat…
PIP Net: Physics-informed Partition Penalty Deep Operator Network
Hongjin Mi, Huiqiang Lun, Changhong Mou +1
Operator learning has become a powerful tool for accelerating the solution of parameterized partial differential equations (PDEs), enabling rapid prediction of full spatiotemporal…
PAS-Net: Physics-informed Adaptive Scale Deep Operator Network
Changhong Mou, Yeyu Zhang, Xuewen Zhu +1
Nonlinear physical phenomena often show complex multiscale interactions; motivated by the principles of multiscale modeling in scientific computing, we propose PAS-Net, a physics-i…