zhong1wan / data-assisted
Code for data-assisted reduced-order modeling of extreme events in complex dynamical systems, available on arXiv: https://arxiv.org/abs/1803.03365
☆21Updated 6 years ago
Alternatives and similar repositories for data-assisted
Users that are interested in data-assisted are comparing it to the libraries listed below
Sorting:
- ☆21Updated 4 years ago
- ☆14Updated 3 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆32Updated last year
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆48Updated 4 years ago
- ☆63Updated 5 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆15Updated last year
- ☆21Updated 2 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- ☆41Updated 7 years ago
- ☆47Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆26Updated 3 years ago
- Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurem…☆37Updated 11 months ago
- Multi-fidelity Generative Deep Learning Turbulent Flows☆38Updated 4 years ago
- Spatio-temporal forecasting of Lorenz96 with RC-ESN, RNN-LSTM and ANN☆41Updated 4 years ago
- ☆41Updated 5 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆29Updated 2 years ago
- ☆24Updated 6 years ago
- This repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"☆19Updated 2 years ago
- Variational Neural Networks for the Solution of Partial Differential Equations☆8Updated 5 years ago
- Physics Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modelling☆23Updated 5 years ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 7 years ago
- Machine learning of linear differential equations using Gaussian processes☆24Updated 7 years ago
- Supporting code for "Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders"☆21Updated 4 years ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆21Updated 2 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆68Updated 4 years ago
- ☆12Updated 2 years ago
- ☆12Updated 3 years ago
- ☆11Updated 3 years ago
- Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" …☆30Updated 2 years ago