37 citations · 39 across the 2 of their papers we have counts for
2 papers
cs.LG2025★ 2 cited
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Zekun Shi, Zheyuan Hu, Min Lin +1
Optimizing neural networks with loss that contain high-dimensional and high-order differential operators is expensive to evaluate with back-propagation due to …
cs.LG2023★ 37 cited
Hutchinson Trace Estimation for High-Dimensional and High-Order Physics-Informed Neural Networks
Zheyuan Hu, Zekun Shi, George Em Karniadakis +1
Physics-Informed Neural Networks (PINNs) have proven effective in solving partial differential equations (PDEs), especially when some data are available by seamlessly blending data…