vivekoommen / NPJCOMPUMATS-03747Links
Learning two-phase microstructure evolution using neural operators and autoencoder architectures
☆23Updated last year
Alternatives and similar repositories for NPJCOMPUMATS-03747
Users that are interested in NPJCOMPUMATS-03747 are comparing it to the libraries listed below
Sorting:
- ☆54Updated 2 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆63Updated 2 months ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆11Updated last year
- This is the implementation of the RecFNO.☆20Updated 2 years ago
- Sparse Physics-based and Interpretable Neural Networks☆50Updated 3 years ago
- Code for "Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains"☆20Updated last year
- ☆29Updated 2 years ago
- ☆35Updated 2 years ago
- ☆42Updated 2 years ago
- ☆21Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆35Updated 3 weeks ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆13Updated last year
- ☆10Updated 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…☆40Updated 2 years ago
- PDE Preserved Neural Network☆53Updated 2 months ago
- ☆39Updated 4 months ago
- Pytorch implementation of Bayesian physics-informed neural networks☆60Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆70Updated last year
- ☆21Updated 3 years ago
- Reduced-Order Modeling of Fluid Flows with Transformers☆24Updated 2 years ago
- Multifidelity DeepONet☆34Updated 2 years ago
- Fourier Neural Operators to solve for Allen Cahn PDE equations☆18Updated 3 years ago
- MIONet: Learning multiple-input operators via tensor product☆34Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆73Updated 3 years ago
- ☆56Updated 5 months ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆45Updated 3 weeks ago
- ☆11Updated last week
- Code for Mesh Transformer describes in the EAGLE dataset☆42Updated 4 months ago
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆47Updated 2 years ago
- ☆12Updated 2 years ago