PredictiveScienceLab / pift-paper-2023Links
Physics-informed information field theory - Solve inverse problems with built-in model form uncertainty estimation
☆12Updated last year
Alternatives and similar repositories for pift-paper-2023
Users that are interested in pift-paper-2023 are comparing it to the libraries listed below
Sorting:
- A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.☆27Updated 3 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆35Updated 3 years ago
- Accompanyig code for "Training Physics-Informed Neural Networks: one learning to rule them all?"☆11Updated 2 years ago
- Computing the discrete spectrum of the Koopman operator using Dynamic Mode Decomposition☆10Updated 5 years ago
- Boosting the training of physics informed neural networks with transfer learning☆26Updated 4 years ago
- Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".☆37Updated 3 years ago
- Deep learning assisted dynamic mode decomposition☆20Updated 3 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- A toolbox for Sequential Bayesian Inference in uncertain nonlinear dynamic systems.☆14Updated last year
- ☆32Updated 3 years ago
- MATLAB solver for the deformation of an elastic half-space based on the Boundary Element Method (BEM)☆12Updated last year
- ☆11Updated 4 years ago
- Sonkyo blade benchmark☆18Updated 4 years ago
- AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)☆43Updated 2 years ago
- ☆11Updated 4 years ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆21Updated 3 years ago
- Kolmogorov-Arnold Networks in MATLAB☆50Updated last month
- Implementation of physics informed neural networks with PyTorch☆21Updated 4 years ago
- SK-PINN: Accelerated physics-informed deep learning by smoothing kernel gradients☆20Updated 4 months ago
- An automatic knowledge embedding framework for scientific machine learning☆23Updated 3 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- ☆20Updated 4 years ago
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- Learning Koopman operator by EDMD with trainable dictionary☆26Updated 3 years ago
- Physics-guided Convolutional Neural Network☆66Updated 4 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…☆41Updated 2 years ago
- Consistent Koopman Autoencoders☆74Updated 2 years ago
- when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…☆75Updated 3 years ago
- 用于求解薛定谔方程的数值解☆12Updated last year
- ☆21Updated 4 years ago