anshu957 / OrderChaosHNN
Hamiltonian neural network implementation for Henon Heiles dynamical system learning mix of order and chaos
☆11Updated last year
Alternatives and similar repositories for OrderChaosHNN:
Users that are interested in OrderChaosHNN are comparing it to the libraries listed below
- ☆107Updated 3 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- ☆27Updated 4 years ago
- ☆11Updated 4 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…☆21Updated 2 years ago
- SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations☆21Updated 2 years ago
- ☆20Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 6 months ago
- Hamiltonian Neural Networks for solving Differential Equations☆22Updated 3 years ago
- ☆21Updated 6 months ago
- Deep Bayesian Optimization for Problems with High-Dimensional Structure☆15Updated 2 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆49Updated last year
- ☆10Updated 3 years ago
- ☆72Updated 4 years ago
- ☆22Updated 2 weeks ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆37Updated 2 years ago
- AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers☆21Updated last month
- Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"☆9Updated 2 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- SINDy (Sparse Identification of Nonlinear Dynamics) algorithms☆74Updated 2 years 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
- Code for the paper "Rational neural networks", NeurIPS 2020☆28Updated 4 years ago
- Accompanying code for "Weak form generalized Hamiltonian learning"☆9Updated 4 years ago
- PyTorch implementation of the EQL network, a neural network for symbolic regression☆39Updated 4 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 3 years ago
- The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …☆14Updated 2 years ago