D2NO: efficient handling of heterogeneous input function spaces with distributed deep neural operators
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Publication:6566058
DOI10.1016/J.CMA.2024.117084MaRDI QIDQ6566058
Zecheng Zhang, Lu Lu, Guang Lin, Christian Moya, Hayden Schaeffer
Publication date: 3 July 2024
Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)
Numerical optimization and variational techniques (65K10) Numerical solution to inverse problems in abstract spaces (65J22)
Cites Work
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- Learning partial differential equations via data discovery and sparse optimization
- MIONet: Learning Multiple-Input Operators via Tensor Product
- Reduced Operator Inference for Nonlinear Partial Differential Equations
- Sparse dynamics for partial differential equations
- Reliable extrapolation of deep neural operators informed by physics or sparse observations
- Convergence rate of DeepONets for learning operators arising from advection-diffusion equations
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