Alternatives and similar repositories for Lagrangian_caVAE

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

• sisl / variational_koopman
  Source code for "Deep Variational Koopman Models: Inferring Koopman Observations for Uncertainty-Aware Dynamics Modeling and Control" fro…
  ☆40Updated 6 years ago
• Physics-aware-AI / DiffCoSim
  By introducing a differentiable contact model, DiffCoSim extends the applicability of Lagrangian/Hamiltonian-inspired neural networks to …
  ☆36Updated 2 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆46Updated last year
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆57Updated 2 years ago
• vmartinezalvarez / DyNODE
  DyNODE: Neural Ordinary Differential Equations for Dynamics Modeling in Continuous Control
  ☆23Updated 4 years ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆27Updated last year
• YunzhuLi / CompositionalKoopmanOperators
  [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control
  ☆90Updated 4 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆45Updated 4 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆109Updated 4 years ago
• wuwushrek / physics_constrained_nn
  Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling
  ☆48Updated 3 years ago
• ivandariojr / LyapunovLearning
  ☆40Updated 2 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆34Updated 3 years ago
• samholt / NeuralLaplace
  Neural Laplace: Differentiable Laplace Reconstructions for modelling any time observation with O(1) complexity.
  ☆77Updated 2 months ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• NoemieJaquier / GaBOtorch
  This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.
  ☆52Updated 3 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• cagatayyildiz / oderl
  Experiment code for "Continuous-Time Model-Based Reinforcement Learning"
  ☆54Updated last year
• oxcsml / constrained-diffusion
  ☆21Updated last year
• yuan-yin / CoDA
  Generalizing to New Physical Systems via Context-Informed Dynamics Model
  ☆25Updated last year
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆128Updated 10 months ago
• locuslab / stable_dynamics
  Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)
  ☆33Updated 5 years ago
• DrewSosa / dissipative_hnns
  Training neural networks to disentangle conservative and dissipative dynamics
  ☆10Updated 3 years ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆46Updated 3 years ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆74Updated 2 years ago
• tksmatsubara / symplectic-adjoint-method
  Code for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.
  ☆16Updated 3 years ago
• young-j-park / 18-NeurIPS-APIAE
  ☆21Updated 6 years ago
• ghliu / DeepGSB
  Deep Generalized Schrödinger Bridge, NeurIPS 2022 Oral
  ☆48Updated 2 years ago
• libeanim / contact-symplectic-integrator-network
  Contact-Aware Symplectic Integrator Network
  ☆14Updated 2 years ago
• cambridge-mlg / neural_diffusion_processes
  ☆13Updated 2 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago