PredictiveIntelligenceLab / ImprovedDeepONetsLinks
☆30Updated 3 years ago
Alternatives and similar repositories for ImprovedDeepONets
Users that are interested in ImprovedDeepONets are comparing it to the libraries listed below
Sorting:
- ☆54Updated 3 years ago
- MIONet: Learning multiple-input operators via tensor product☆44Updated 3 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆77Updated 2 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆39Updated 2 years ago
- Separabale Physics-Informed DeepONets in JAX☆21Updated last year
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆10Updated 5 months ago
- Competitive Physics Informed Networks☆32Updated last year
- ☆36Updated 6 months ago
- POD-PINN code and manuscript☆57Updated last year
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆76Updated 9 months ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆30Updated last year
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- XPINN code written in TensorFlow 2☆28Updated 3 years ago
- Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)☆34Updated 2 years ago
- PDE Preserved Neural Network☆59Updated 8 months ago
- ☆15Updated 4 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆92Updated 5 years ago
- Code accompanying "Inverse-Dirichlet Weighting Enables Reliable Training of Physics Informed Neural Networks", Maddu et al., 2021☆14Updated 4 years ago
- A sequential DeepONet model implementation that uses a recurrent neural network (GRU and LSTM) in the branch and a feed-forward neural ne…☆19Updated last year
- 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
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆37Updated 2 months ago
- ☆110Updated 4 years ago
- hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations☆87Updated 5 months ago
- Implementation of the deep operator network in pytorch, with examples of solving Differential Equations☆17Updated last year
- ☆13Updated 3 weeks ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 4 years ago
- ☆13Updated 2 years ago
- Discontinuity Computing Using Physics-Informed Neural Network☆27Updated last year