PredictiveIntelligenceLab / BayesianDifferentiableProgrammingLinks
☆21Updated 4 years ago
Alternatives and similar repositories for BayesianDifferentiableProgramming
Users that are interested in BayesianDifferentiableProgramming are comparing it to the libraries listed below
Sorting:
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆56Updated 3 years ago
- Sparse Identification of Nonlinear Dynamics for Hybrid Systems☆25Updated 7 years ago
- ☆29Updated 7 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems☆30Updated 3 years ago
- a collection of modern sparse (regularized) linear regression algorithms.☆64Updated 5 years ago
- combination of sparse identification of nonlinear dynamics with Akaike information criteria☆16Updated 8 years ago
- Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]☆32Updated last year
- Update PDEKoopman code to Tensorflow 2☆23Updated 4 years ago
- Stiff Neural Ordinary Differential Equations☆34Updated 2 years ago
- ☆14Updated 3 years ago
- ☆29Updated 2 years ago
- ☆21Updated 2 years ago
- Multi Fidelity Monte Carlo☆24Updated 5 years ago
- ☆42Updated 5 years ago
- An integrated demo: Gaussian processes for PDEs and inverse problems☆14Updated last month
- GPTIPS2F: Symbolic Regression toolbox for MATLAB evolved☆11Updated 3 years ago
- Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data☆49Updated 5 years ago
- Deep renormalized Mori-Zwanzig (DrMZ) Julia package.☆17Updated 2 years ago
- Codes for Linear and Nonlinear Disambiguation Optimization (LANDO)☆29Updated 3 years ago
- This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…☆21Updated 10 months ago
- Tutorial on Gaussian Processes☆62Updated 5 years ago
- TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks…☆20Updated 2 years ago
- ☆18Updated 4 years ago
- ☆41Updated 7 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆35Updated 3 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
- Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)☆57Updated 4 years ago
- Code for the paper: Solving and Learning Nonlinear PDEs with Gaussian Processes☆39Updated last month