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math.NA2024
Annealed adaptive importance sampling method in PINNs for solving high dimensional partial differential equations
Zhengqi Zhang, Jing Li, Bin Liu
Physics-informed neural networks (PINNs) have emerged as powerful tools for solving a wide range of partial differential equations (PDEs). However, despite their user-friendly inte…
math.NA2023
Data Generation-based Operator Learning for Solving Partial Differential Equations on Unbounded Domains
Jihong Wang, Xin Wang, Jing Li +1
Wave propagation problems are typically formulated as partial differential equations (PDEs) on unbounded domains to be solved. The classical approach to solving such problems invol…