ETH-WindMil / JSD-SBILinks
A toolbox for Sequential Bayesian Inference in uncertain nonlinear dynamic systems.
☆15Updated last year
Alternatives and similar repositories for JSD-SBI
Users that are interested in JSD-SBI are comparing it to the libraries listed below
Sorting:
- Deep learning assisted dynamic mode decomposition☆19Updated 4 years ago
- Sonkyo blade benchmark☆18Updated 4 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆78Updated 3 years ago
- ☆37Updated 2 years ago
- mathLab mirror of Python Dynamic Mode Decomposition☆106Updated 7 months ago
- Identification of Bouc–Wen type models using the transitional Markov chain Monte Carlo method☆14Updated 7 months ago
- ☆131Updated 3 years ago
- ☆13Updated last year
- We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.☆96Updated 2 years ago
- ☆87Updated 2 years ago
- Physics-guided Convolutional Neural Network☆68Updated 5 years ago
- Research/development of physics-informed neural networks for dynamic systems☆29Updated 11 months ago
- Physics-informed neural networks package☆330Updated 3 years ago
- Data-driven reduced order modeling for nonlinear dynamical systems☆90Updated 4 months ago
- ☆11Updated 2 years ago
- Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)☆31Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Hands-on tutorial for implementing Physics Informed Neural Networks in Pytorch☆53Updated 6 months ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆38Updated 3 years ago
- Physics-guided Deep Markov Models☆12Updated 3 years ago
- Pytorch implementation of Bayesian physics-informed neural networks☆64Updated 4 years ago
- ☆14Updated 3 years ago
- Simulation of a SDOF Bouc-Wen-Baber-Noori hysteretic system☆13Updated 4 years ago
- Discovers high dimensional models from 1D data using deep delay autoencoders☆37Updated 2 years ago
- Computing the discrete spectrum of the Koopman operator using Dynamic Mode Decomposition☆10Updated 5 years ago
- Tutorials and examples of advanced sampling methods for solving Bayesian Model Updating Problems☆39Updated last year
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 4 years ago
- MATLAB codes for physics-informed dynamic mode decomposition (piDMD)☆161Updated last year
- An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification☆35Updated 7 months ago
- Supporting codes for the numerical implementations in the paper "Operator inference for non-intrusive model reduction with quadratic mani…☆11Updated 3 years ago