2 papers
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.NA2023
A novel reduced basis method for adjoint sensitivity analysis of dynamic topology optimization
Shuhao Li, Hu Wang, Jichao Yin +2
In gradient-based time domain topology optimization, design sensitivity analysis (DSA) of the dynamic response is essential, and requires high computational cost to directly differ…