Multi-fidelity surrogate modeling using long short-term memory networks. (arXiv:2208.03115v2 [math.NA] UPDATED)

When evaluating quantities of interest that depend on the solutions to
differential equations, we inevitably face the trade-off between accuracy and
efficiency. Especially for parametrized, time dependent problems in engineering
computations, it is often the case that acceptable computational budgets limit
the availability of high-fidelity, accurate simulation data. Multi-fidelity
surrogate modeling has emerged as an effective strategy to overcome this
difficulty. Its key idea is to leverage many low-fidelity simulation data, less
accurate but much faster to compute, to improve …

arxiv fidelity long short-term memory math memory modeling networks