An alternating low-rank projection approach for partial differential
equations with random inputs
An alternating low-rank projection approach for partial differential
equations with random inputs
It is known that standard stochastic Galerkin methods face challenges when solving partial differential equations (PDEs) with random inputs. These challenges are typically attributed to the large number of required physical basis functions and stochastic basis functions. Therefore, it becomes crucial to select effective basis functions to properly reduce the …