DurstewitzLab / ChaosRNN
☆15Updated 2 years ago
Alternatives and similar repositories for ChaosRNN:
Users that are interested in ChaosRNN are comparing it to the libraries listed below
- Python package to compute Lyapunov exponents, covariant Lyapunov vectors (CLV) and adjoints of a dynamical systems.☆17Updated last year
- Quantification of Uncertainties in Neural Networks☆11Updated 4 months ago
- Fractional White Noises for Neural Stochastic Differential Equations (NeurIPS 2022)☆14Updated 2 years ago
- ☆11Updated 3 years ago
- PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning☆34Updated 3 years ago
- Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems☆21Updated this week
- Try to approximate the solution of Fokker-Planck equation☆9Updated last year
- An unofficial implementation of the Fourier Neural Operator in Flax☆17Updated 9 months ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆18Updated last week
- ☆19Updated 2 years ago
- ☆29Updated 9 months ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆20Updated 2 years ago
- Spatio-temporal forecasting of Lorenz96 with RC-ESN, RNN-LSTM and ANN☆40Updated 4 years ago
- ☆47Updated last year
- Python 2D Navier-Stokes solver☆15Updated last month
- Efficient Differentiable n-d PDE solvers in JAX.☆24Updated 4 months ago
- Code for "Nonlinear stochastic modeling with Langevin regression" J. L. Callaham, J.-C. Loiseau, G. Rigas, and S. L. Brunton☆25Updated 3 years ago
- ☆39Updated 2 years ago
- Multi-fidelity Bayesian Optimization via Deep Neural Nets☆29Updated 4 years ago
- ☆15Updated 7 months ago
- [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.☆30Updated 8 months ago
- Pseudospectral Kolmogorov Flow Solver☆37Updated last year
- Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems☆13Updated 9 months ago
- A data-driven method to calculate the Lyapunov exponent of a dynamical system employing a GRU-RNN.☆41Updated 7 months ago
- Machine learning algorithms for discovering dimensionless groups from simulation and experimental data☆11Updated 2 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics☆49Updated 2 years ago
- ☆35Updated last year
- Code for the paper "Rational neural networks", NeurIPS 2020☆28Updated 4 years ago