mfinzi / constrained-hamiltonian-neural-networksLinks
☆112Updated 4 years ago
Alternatives and similar repositories for constrained-hamiltonian-neural-networks
Users that are interested in constrained-hamiltonian-neural-networks are comparing it to the libraries listed below
Sorting:
- Symplectic Recurrent Neural Networks☆28Updated 2 years ago
- Refining continuous-in-depth neural networks☆42Updated 4 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- This repository contains code released by DiffEqML Research☆92Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…☆69Updated last year
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 3 years ago
- ☆21Updated 3 years ago
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆88Updated 3 years ago
- ☆23Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆41Updated 3 years ago
- ☆47Updated 5 years ago
- Turning SymPy expressions into PyTorch modules.☆156Updated 2 years ago
- Port-Hamiltonian Approach to Neural Network Training☆26Updated 6 years ago
- Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"☆61Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- ☆30Updated 2 weeks ago
- Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight☆55Updated 4 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆20Updated last year
- ☆105Updated 4 years ago
- Learning unknown ODE models with Gaussian processes☆27Updated 7 years ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆287Updated 4 years ago
- ☆28Updated 3 years ago
- ☆30Updated 3 years ago
- Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"☆56Updated 2 years ago
- repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE☆57Updated 4 years ago
- Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.☆19Updated 4 years ago
- ☆36Updated 4 years ago
- A Python package to learn the Koopman operator.☆65Updated 3 weeks ago