Alternatives and similar repositories for HamiltonianNet:

Users that are interested in HamiltonianNet are comparing it to the libraries listed below

• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆34Updated 2 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated last year
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆51Updated 3 years ago
• steindoringi / Variational_Integrator_Networks
  ☆19Updated 2 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆45Updated 4 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆21Updated last month
• ivandariojr / LyapunovLearning
  ☆39Updated last year
• tksmatsubara / symplectic-adjoint-method
  Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.
  ☆16Updated 3 years ago
• wzhi / ODElearning_INN
  [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks
  ☆10Updated last year
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆34Updated 3 years ago
• imbirik / LieStationaryKernels
  Supplementary code for the paper "Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces"
  ☆42Updated last year
• nash169 / manifold-gp
  Repository containing the code for Implicit Manifold Gaussian Process.
  ☆14Updated 7 months ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• yzshi5 / OpFlow
  codes for "Universal Functional Regression with Neural Operator Flows"
  ☆13Updated 5 months ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆106Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• jpzxshi / sympnets
  ☆27Updated 3 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆45Updated 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
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆24Updated last year
• yiminzme / awesome-bayesian-optimization
  a curated list of bayesian optimization tutorials, papers, softwares
  ☆28Updated 3 years ago
• NoemieJaquier / MaternGaBO
  This repository contains the code for the paper "Geometry-aware Bayesian Optimization in Roboticsusing Riemannian Matérn Kernels" (CoRL'2…
  ☆19Updated last year
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆45Updated last year
• alexOarga / haiku-geometric
  A collection of graph neural networks implementations in JAX
  ☆32Updated last year
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 4 years ago