Adaptive collocation sampling and learned loss weights improve accuracy of quantum physics-informed neural networks on six differential-equation benchmarks, including Burgers and Navier-Stokes flows.
Garc \'i a-Pe \ n alvo
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Adaptive Quantum Physics-Informed Neural Networks for Differential Equations with Applications to Fluid Dynamics
Adaptive collocation sampling and learned loss weights improve accuracy of quantum physics-informed neural networks on six differential-equation benchmarks, including Burgers and Navier-Stokes flows.