jtoleary / SPINODELinks
Stochastic Physics-Informed Neural Ordinary Differential Equations
☆19Updated 3 years ago
Alternatives and similar repositories for SPINODE
Users that are interested in SPINODE are comparing it to the libraries listed below
Sorting:
- ☆14Updated 4 years ago
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants. Proceedings of the Royal S…☆11Updated last year
- To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…☆52Updated 3 years ago
- Reduced order modeling with shallow recurrent decoder networks☆19Updated 3 weeks ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆20Updated 2 years ago
- Neural Galerkin☆16Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆83Updated 3 years ago
- Transformed Generative Pre-Trained Physics-Informed Neural Networks (TGPT-PINN), a framework that extends Physics-Informed Neural Network…☆18Updated last year
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Implementing a physics-informed DeepONet from scratch☆56Updated 2 years ago
- Sample codes of CNN-SINDy based reduced-order modeling for fluid flows by Fukami et al., JFM 2021.☆29Updated 4 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆36Updated 4 years ago
- Solving High Dimensional Partial Differential Equations with Deep Neural Networks☆34Updated 4 years ago
- ☆13Updated 3 years ago
- Official Code for ICML 2024 paper "TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision"☆18Updated last year
- This repository contains the code and models for our paper "Investigating and Mitigating Failure Modes in Physics-informed Neural Network…☆19Updated 2 years ago
- Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."☆76Updated 9 months ago
- Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs☆32Updated 4 years ago
- Stochastic Physics-Informed Neural Networks: A Moment-Matching Framework for Learning Hidden Physics within Stochastic Differential Equat…☆14Updated 4 years ago
- ☆130Updated 3 years ago
- PROSE: Predicting Multiple Operators and Symbolic Expressions☆32Updated 3 months ago
- Original implementation of fast PINN optimization with RBA weights☆69Updated 5 months ago
- SINDy-SA framework: enhancing nonlinear system identification with sensitivity analysis☆12Updated 9 months ago
- PECANNs: Physics and Equality Constrained Artificial Neural Networks☆24Updated 2 years ago
- Physics-encoded recurrent convolutional neural network☆48Updated 4 years ago
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆45Updated 3 years ago
- 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 3 months ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆28Updated last year