Randomized neural operator for parametric PDEs with fast training and conformal uncertainty quantification
DGX agentarXiv:2606.29440v1 Announce Type: new Abstract: Repeatedly solving parametric PDEs is essential for uncertainty quantification, design optimization and inverse problems, but conventional neural operat