cb-sjtu / Decoder_DeepONetLinks
A hybrid Decoder-DeepONet operator regression framework for unaligned observation data
☆10Updated 2 years ago
Alternatives and similar repositories for Decoder_DeepONet
Users that are interested in Decoder_DeepONet are comparing it to the libraries listed below
Sorting:
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆54Updated 2 years ago
- ☆26Updated 3 years ago
- Gradient-based adaptive sampling algorithms for self-supervising PINNs☆28Updated 2 years ago
- ☆68Updated 3 years ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆167Updated last year
- Physics Informed Fourier Neural Operator☆26Updated last year
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆28Updated 11 months ago
- A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks☆96Updated 3 years ago
- PDE Preserved Neural Network☆59Updated 7 months ago
- ☆164Updated 3 years ago
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆11Updated 4 months ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Updated 2 years ago
- ☆54Updated 3 years ago
- Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems☆59Updated 3 years ago
- Original implementation of fast PINN optimization with RBA weights☆68Updated 4 months ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆38Updated 2 years ago
- Physics-informed deep super-resolution of spatiotemporal data☆49Updated 2 years ago
- Physics-Informed Neural Network (PINN) for Solving Coupled PDEs Governing Thermochemical Physics in Bi-Material Systems☆60Updated 5 years ago
- A pytorch implementation of several approaches using PINN to slove turbulent flow☆89Updated last year
- POD-PINN code and manuscript☆57Updated last year
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆75Updated 2 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆69Updated 4 years ago
- This repository contains the code for the paper: Deciphering and integrating invariants for neural operator learning with various physica…☆13Updated last year
- Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting☆38Updated 2 years ago
- ☆29Updated 3 years ago
- PhyGeoNet: Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Parametric PDEs on Irregular Domain☆91Updated 4 years ago
- Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning☆93Updated 2 years ago
- Physics Informed Neural Network (PINN) for the 2D Navier-Stokes equation☆37Updated 3 years ago
- MIONet: Learning multiple-input operators via tensor product☆43Updated 3 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆107Updated 3 years ago