Zhengyu-Huang / Operator-LearningLinks
☆44Updated 3 years ago
Alternatives and similar repositories for Operator-Learning
Users that are interested in Operator-Learning are comparing it to the libraries listed below
Sorting:
- ☆29Updated last year
- ☆13Updated 2 years ago
- An extension of Fourier Neural Operator to finite-dimensional input and/or output spaces.☆19Updated 3 months ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- ☆41Updated 2 years ago
- ☆54Updated 3 years ago
- Practicum on Supervised Learning in Function Spaces☆34Updated 3 years ago
- Spectral Neural Operator☆79Updated 2 years ago
- Pseudospectral Kolmogorov Flow Solver☆42Updated 2 years ago
- Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning☆17Updated 2 years ago
- PyTorch implemention of the Position-induced Transformer for operator learning in partial differential equations☆25Updated 8 months ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- MIONet: Learning multiple-input operators via tensor product☆44Updated 3 years ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆15Updated last year
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 11 months ago
- ☆15Updated 4 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆72Updated 2 months ago
- ☆40Updated last year
- ☆30Updated 3 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆20Updated last year
- ☆90Updated last year
- [NeurIPS 2025] Geometry Aware Operator Transformer As An Efficient And Accurate Neural Surrogate For PDEs On Arbitrary Domains☆73Updated 3 months ago
- ☆49Updated 10 months ago
- Dimension reduced surrogate construction for parametric PDE maps☆39Updated 5 months ago
- Code of ICML paper arxiv.org/abs/2302.08105☆14Updated 2 years ago
- Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…☆43Updated 3 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆76Updated 9 months ago
- Separabale Physics-Informed DeepONets in JAX☆21Updated last year
- ☆10Updated 2 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆28Updated last year