martius-lab / EQL_TensorflowLinks
Tensorflow implementation of equation learner
☆32Updated 4 years ago
Alternatives and similar repositories for EQL_Tensorflow
Users that are interested in EQL_Tensorflow are comparing it to the libraries listed below
Sorting:
- Equation Learner, a neural network approach to symbolic regression☆82Updated 11 months ago
- SINDy (Sparse Identification of Nonlinear Dynamics) algorithms☆79Updated 2 years ago
- Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems☆63Updated 5 years ago
- Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations☆155Updated 5 years ago
- ☆73Updated 5 years ago
- Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations☆69Updated 5 years ago
- Port-Hamiltonian Approach to Neural Network Training☆24Updated 5 years ago
- Official repository for the paper "Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery"☆76Updated 2 years ago
- ☆41Updated 7 years ago
- ☆21Updated 4 years ago
- Multi Fidelity Monte Carlo☆24Updated 5 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆56Updated 3 years ago
- kramersmoyal: Kramers-Moyal coefficients for stochastic data of any dimension, to any desired order☆74Updated 8 months ago
- a collection of modern sparse (regularized) linear regression algorithms.☆64Updated 5 years ago
- Code for the paper "Rational neural networks", NeurIPS 2020☆27Updated 4 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year
- RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical sy…☆95Updated 2 years ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆26Updated 3 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆41Updated 4 years ago
- ☆176Updated 2 years ago
- ☆30Updated 7 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆15Updated 2 years ago
- ☆30Updated 4 years ago
- Solving stochastic differential equations and Kolmogorov equations by means of deep learning and Multilevel Monte Carlo simulation☆12Updated 4 years ago
- Code repository for the paper "Learning partial differential equations for biological transport models from noisy spatiotemporal data"☆10Updated 6 years ago
- ☆110Updated 4 years ago
- A hands-on tutorial on supervised learning with Gaussian processes☆38Updated 5 years ago
- ☆116Updated 6 years ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 11 months ago
- ☆42Updated 5 years ago