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math.NA2023
Resolution-independent generative models based on operator learning for physics-constrained Bayesian inverse problems
Xinchao Jiang, Xin Wang, Ziming Wen +1
The Bayesian inference approach is widely used to tackle inverse problems due to its versatile and natural ability to handle ill-posedness. However, it often faces challenges when…
math.NA2022★ 3 cited
An E-PINN assisted practical uncertainty quantification for inverse problems
Xinchao Jiang, Xin Wanga, Ziming Wena +2
How to solve inverse problems is the challenge of many engineering and industrial applications. Recently, physics-informed neural networks (PINNs) have emerged as a powerful approa…