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…