Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
☆78Apr 24, 2025Updated 10 months ago
Alternatives and similar repositories for latent-deeponet
Users that are interested in latent-deeponet are comparing it to the libraries listed below
Sorting:
- DON-LSTM: Multi-Resolution Learning with DeepONets and Long-Short Term Memory Neural Networks☆10Sep 4, 2025Updated 6 months ago
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆21Jun 20, 2024Updated last year
- ☆10Mar 18, 2023Updated 2 years ago
- A hybrid Decoder-DeepONet operator regression framework for unaligned observation data☆10Jul 16, 2023Updated 2 years ago
- ☆26Jul 7, 2022Updated 3 years ago
- ☆28Jan 19, 2026Updated last month
- ☆13Aug 22, 2024Updated last year
- ☆17Aug 13, 2024Updated last year
- Separabale Physics-Informed DeepONets in JAX☆21Nov 29, 2024Updated last year
- ☆11Jan 7, 2025Updated last year
- Implementation of the deep operator network in pytorch, with examples of solving Differential Equations☆17Mar 30, 2024Updated last year
- ☆31Oct 6, 2022Updated 3 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆76Nov 21, 2025Updated 3 months ago
- A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data☆361Jul 14, 2023Updated 2 years ago
- Repository for sharing code and data assocaited with En-DeepONet architecture☆35Jan 15, 2024Updated 2 years ago
- This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs☆210Nov 24, 2025Updated 3 months ago
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆40Mar 10, 2025Updated 11 months ago
- ☆26Jun 12, 2025Updated 8 months ago
- ☆12May 3, 2023Updated 2 years ago
- ☆91Sep 2, 2024Updated last year
- Reliable extrapolation of deep neural operators informed by physics or sparse observations☆28Jun 4, 2023Updated 2 years ago
- Papers and codes of Physics-informed Deep Compositional Operator Network☆13Oct 31, 2025Updated 4 months ago
- ☆32Sep 13, 2025Updated 5 months ago
- ☆35Jan 5, 2024Updated 2 years ago
- ☆24Dec 21, 2023Updated 2 years ago
- ☆54Jul 21, 2025Updated 7 months ago
- ☆512Apr 1, 2025Updated 11 months ago
- ☆55Oct 9, 2022Updated 3 years ago
- This is the implementation of the RecFNO.☆25Feb 21, 2023Updated 3 years ago
- ☆1,080Jan 29, 2026Updated last month
- Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.☆78Aug 4, 2023Updated 2 years ago
- Learning two-phase microstructure evolution using neural operators and autoencoder architectures☆26Apr 25, 2024Updated last year
- Reduced-Order Modeling of Fluid Flows with Transformers☆25May 30, 2023Updated 2 years ago
- Prediction of Fluid Flow in Porous Media by Sparse Observations and Physics-Informed PointNet☆14Aug 24, 2024Updated last year
- About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664☆80Apr 10, 2025Updated 11 months ago
- Implementation of Physics-Informed Diffusion Models (ICLR 2025)☆195Feb 1, 2026Updated last month
- ☆293Sep 14, 2024Updated last year
- Official implementation of "PhyGNNet: Solving spatiotemporal PDEs with Physics-informed Graph Neural Network"☆54May 30, 2023Updated 2 years ago
- Physics Informed Fourier Neural Operator☆30Nov 21, 2024Updated last year