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

• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆85Updated 2 years ago
• martenlienen / finite-element-networks
  Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…
  ☆70Updated 8 months ago
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆49Updated last year
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆57Updated 4 months ago
• Physics-aware-AI / Symplectic-ODENet
  ☆44Updated 4 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆42Updated last year
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated 11 months ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆82Updated 3 years ago
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆18Updated 2 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆34Updated 3 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆44Updated 3 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆145Updated last year
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆36Updated 2 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆54Updated 3 years ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆115Updated last year
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆27Updated 2 years ago
• jpzxshi / sympnets
  ☆26Updated 3 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆169Updated 3 years ago
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆49Updated 2 years ago
• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated last year
• coursekevin / weakformghnn
  Accompanying code for "Weak form generalized Hamiltonian learning"
  ☆9Updated 4 years ago
• steindoringi / Variational_Integrator_Networks
  ☆18Updated 2 years ago
• samholt / NeuralLaplace
  Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
  ☆74Updated last month
• j-wilson / GPflowSampling
  Code for efficiently sampling functions from GP(flow) posteriors
  ☆69Updated 4 years ago
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆48Updated last year
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆134Updated last year
• ucl-bug / jaxdf
  A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations
  ☆124Updated 5 months ago