3 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
D2NO: Efficient Handling of Heterogeneous Input Function Spaces with Distributed Deep Neural Operators
Zecheng Zhang, Christian Moya, Lu Lu +2
Neural operators have been applied in various scientific fields, such as solving parametric partial differential equations, dynamical systems with control, and inverse problems. Ho…
Bayesian deep operator learning for homogenized to fine-scale maps for multiscale PDE
Zecheng Zhang, Christian Moya, Wing Tat Leung +2
We present a new framework for computing fine-scale solutions of multiscale Partial Differential Equations (PDEs) using operator learning tools. Obtaining fine-scale solutions of m…
A discretization-invariant extension and analysis of some deep operator networks
Zecheng Zhang, Wing Tat Leung, Hayden Schaeffer
We present a generalized version of the discretization-invariant neural operator and prove that the network is a universal approximation in the operator sense. Moreover, by incorpo…