Implementing a physics-informed DeepONet from scratch
☆63Jul 9, 2023Updated 3 years ago
Alternatives and similar repositories for PI-DeepONet
Users that are interested in PI-DeepONet are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- Separabale Physics-Informed DeepONets in JAX☆28Nov 29, 2024Updated last year
- ☆426Dec 3, 2022Updated 3 years ago
- A Deep Learning Approach to Solving PDEs: Implementing Neural Networks with Pytorch and Jax☆10Apr 27, 2023Updated 3 years ago
- Multifidelity deep neural operators for efficient learning of partial differential equations with application to fast inverse design of n…☆42Jul 12, 2023Updated 3 years ago
- ☆27Jul 7, 2022Updated 4 years ago
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click. Zero configuration with optimized deployments.
- ☆16Oct 25, 2021Updated 4 years ago
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆29Jun 4, 2023Updated 3 years ago
- Implementation of the deep operator network in pytorch, with examples of solving Differential Equations☆17Mar 30, 2024Updated 2 years ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆394Jul 14, 2023Updated 3 years ago
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆84Aug 4, 2023Updated 3 years ago
- A collection of Jupyter notebooks providing tutorials on reduced order modeling techniques like DeepONet, FNO, DL-ROM, and POD-DL-ROM. Ea…☆32Jan 20, 2025Updated last year
- ☆19Aug 13, 2024Updated 2 years ago
- Discovering Differential Equations with Physics-Informed Neural Networks and Symbolic Regression☆11Jul 28, 2023Updated 3 years ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆22Jun 20, 2024Updated 2 years ago
- Bare Metal GPUs on DigitalOcean Gradient AI • AdPurpose-built for serious AI teams training foundational models, running large-scale inference, and pushing the boundaries of what's possible.
- Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators☆835Jun 25, 2022Updated 4 years ago
- PINN Implementation for IJCAI paper, "Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activat…☆22Jun 19, 2024Updated 2 years ago
- Contains implementation of PINN using Tensorflow 2.4.0☆14Apr 28, 2023Updated 3 years ago
- Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.☆41Nov 2, 2024Updated last year
- Original implementation of fast PINN optimization with RBA weights☆77Sep 11, 2025Updated 11 months ago
- Using knowledge-guided machine learning to assess patterns of areal change in waterbodies across the contiguous US☆10Mar 28, 2024Updated 2 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆86Apr 24, 2025Updated last year
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆293Sep 28, 2024Updated last year
- Implementations of three neural operators and application in Bayesian inference problems☆18Jul 5, 2026Updated last month
- Managed Kubernetes at scale on DigitalOcean • AdDigitalOcean Kubernetes includes the control plane, bandwidth allowance, container registry, automatic updates, and more for free.
- Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robus…☆39Dec 29, 2023Updated 2 years ago
- Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems☆114Apr 15, 2022Updated 4 years ago
- 本项目利用pytorch实现了一个简易的模块化DeepONet,凭此可以快速的实现一些简易的DeepONet。☆18Jul 2, 2025Updated last year
- ☆17Jan 18, 2024Updated 2 years ago
- ☆14Jun 3, 2024Updated 2 years ago
- ☆33Oct 6, 2022Updated 3 years ago
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆15May 27, 2024Updated 2 years ago
- Physics Informed Machine Learning Tutorials (Pytorch and Jax)☆680May 31, 2026Updated 2 months ago
- Data-guided physics-informed neural networks☆18Jul 16, 2024Updated 2 years ago
- Serverless GPU API endpoints on Runpod - Get Bonus Credits • AdSkip the infrastructure headaches. Auto-scaling, pay-as-you-go, no-ops approach lets you focus on innovating your application.
- ☆226Jul 27, 2024Updated 2 years ago
- Neural Operators with Applications to the Helmholtz Equation☆11Sep 19, 2024Updated last year
- Physics-informed neural networks to solve forward and inverse problems of 1D laminar flames☆21Mar 4, 2025Updated last year
- Active learning of extreme events using deep neural operators.☆17Nov 10, 2022Updated 3 years ago
- ☆222Feb 16, 2024Updated 2 years ago
- DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia☆39Aug 6, 2026Updated last week
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆82Nov 21, 2025Updated 8 months ago