Physics-aware-AI / Symplectic-ODENet
☆45Updated 4 years ago
Alternatives and similar repositories for Symplectic-ODENet:
Users that are interested in Symplectic-ODENet are comparing it to the libraries listed below
- A framework for neural network control of dynamical systems over graphs.☆58Updated 2 years ago
- Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"☆18Updated 2 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- ☆15Updated 4 years ago
- [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control☆88Updated 4 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling☆48Updated 3 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆46Updated 3 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆51Updated 3 years ago
- ☆29Updated 2 years ago
- ☆107Updated 3 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 2 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 5 years ago
- Consistent Koopman Autoencoders☆74Updated last year
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆26Updated last year
- Offline Contextual Bayesian Optimization☆14Updated last year
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- Nonparametric Differential Equation Modeling☆53Updated last year
- Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…☆39Updated 5 years ago
- By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …☆35Updated 2 years ago
- Experiment code for "Continuous-Time Model-Based Reinforcement Learning"☆52Updated last year
- ☆19Updated 2 years ago
- This repository contains code released by DiffEqML Research☆90Updated 3 years ago
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 3 years ago
- Port-Hamiltonian Approach to Neural Network Training☆22Updated 5 years ago
- IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control☆45Updated 4 years ago
- project for my essay on how to use neural networks to linearise nonlinear dynamical systems☆9Updated 4 years ago
- ☆50Updated 6 years ago
- This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.☆26Updated last week
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 6 months ago