gaoliyao / sindy-shredLinks
Code for paper Sparse identification of nonlinear dynamics with Shallow Recurrent Decoder Networks.
☆34Updated last month
Alternatives and similar repositories for sindy-shred
Users that are interested in sindy-shred are comparing it to the libraries listed below
Sorting:
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆35Updated 9 months ago
- A library for dimensionality reduction on spatial-temporal PDE☆70Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆81Updated 3 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆75Updated 7 months ago
- ☆47Updated 3 months ago
- mathLab mirror of Python Dynamic Mode Decomposition☆110Updated 9 months ago
- Pseudospectral Kolmogorov Flow Solver☆41Updated 2 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year
- Benchmarking Autoregressive Conditional Diffusion Models for Turbulent Flow Simulation☆100Updated last year
- ☆14Updated 3 years ago
- implementation of physics-informed variational auto-encoder☆20Updated 2 years ago
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆59Updated 4 years ago
- ☆113Updated last year
- GCA-ROM is a library which implements graph convolutional autoencoder architecture as a nonlinear model order reduction strategy.☆36Updated last month
- Simple demo on implementing data driven and physics informed Deep O Nets in pytorch☆19Updated last year
- Deep learning assisted dynamic mode decomposition☆19Updated 4 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆27Updated 4 years ago
- Sparse Physics-based and Interpretable Neural Networks☆52Updated 4 years ago
- SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis☆12Updated 7 months ago
- ☆197Updated 8 months ago
- ☆12Updated 3 years ago
- PDE Preserved Neural Network☆58Updated 7 months ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- [ICLR 2025] Neural Operator-Assisted Computational Fluid Dynamics in PyTorch☆68Updated 3 weeks ago
- Physics-informed neural networks☆16Updated 5 years ago
- ☆12Updated 2 weeks ago
- Practicum on Supervised Learning in Function Spaces☆33Updated 3 years ago
- We present cod-bench containing 12 operators and 10 datasets.☆11Updated last year
- Codes associated with the manuscript titled "Multi-stage neural networks: Function approximator of machine precision"☆49Updated last year