Zymrael / PortHamiltonianNN
Port-Hamiltonian Approach to Neural Network Training
☆22Updated 5 years ago
Alternatives and similar repositories for PortHamiltonianNN:
Users that are interested in PortHamiltonianNN are comparing it to the libraries listed below
- Nonparametric Differential Equation Modeling☆53Updated last year
- ☆29Updated 2 years ago
- ☆23Updated 4 years ago
- ☆45Updated 4 years ago
- Accompanying code for "Weak form generalized Hamiltonian learning"☆9Updated 4 years ago
- Refining continuous-in-depth neural networks☆39Updated 3 years ago
- Learning unknown ODE models with Gaussian processes☆26Updated 6 years ago
- Data-driven dynamical systems toolbox.☆74Updated last week
- Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…☆21Updated 2 years ago
- A PyTorch library for all things nonlinear control and reinforcement learning.☆46Updated 3 years ago
- Repository for Deterministic Particle Flow Control framework☆10Updated 2 years ago
- Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…☆54Updated 2 years ago
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- Sparse Identification of Nonlinear Dynamics for Hybrid Systems☆23Updated 6 years ago
- Code accompanying the ICLR 2021 paper "ResNet After All? Neural ODEs and Their Numerical Solution"☆9Updated 2 years ago
- ☆37Updated 3 years ago
- This repository contains code released by DiffEqML Research☆90Updated 3 years ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆10Updated 2 years ago
- Methods and experiments for assumed density SDE approximations☆11Updated 3 years ago
- Koopman Kernels for Learning Dynamical Systems from Trajectory Data☆26Updated last year
- ☆107Updated 3 years ago
- Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.☆16Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- Neural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248☆16Updated last year
- ☆30Updated 2 years ago
- Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes☆12Updated 2 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆58Updated 6 months ago
- ☆27Updated 4 years ago
- Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting☆45Updated last year
- ☆10Updated 3 years ago