Alternatives and similar repositories for OrderChaosHNN:

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

• mfinzi / constrained-hamiltonian-neural-networks
  ☆106Updated 3 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 2 years ago
• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆28Updated 2 years ago
• luckystarufo / multiscale_HiTS
  ☆72Updated 4 years ago
• cselab / LED
  ☆19Updated 2 years ago
• lorenzrichter / PDE-backward-solver
  ☆21Updated 5 months ago
• jpzxshi / sympnets
  ☆27Updated 3 years ago
• Zymrael / PortHamiltonianNN
  Port-Hamiltonian Approach to Neural Network Training
  ☆22Updated 5 years ago
• PredictiveIntelligenceLab / JAX-BO
  ☆30Updated 2 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• NBoulle / RationalNets
  Code for the paper "Rational neural networks", NeurIPS 2020
  ☆28Updated 4 years ago
• facebookresearch / neural-conservation-law
  code for "Neural Conservation Laws A Divergence-Free Perspective".
  ☆37Updated 2 years ago
• coursekevin / weakformghnn
  Accompanying code for "Weak form generalized Hamiltonian learning"
  ☆9Updated 4 years ago
• peterparity / symder
  SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
  ☆20Updated 2 years ago
• mariosmat / hamiltonianNNetODEs
  Hamiltonian Neural Networks for solving Differential Equations
  ☆21Updated 3 years ago
• juliusberner / deep_kolmogorov
  Numerically Solving Parametric Families of High-Dimensional Kolmogorov Partial Differential Equations via Deep Learning (NeurIPS 2020)
  ☆22Updated 2 years ago
• lorenzrichter / path-space-PDE-solver
  ☆10Updated 3 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 6 years ago
• DENG-MIT / StiffNet-Benchmark
  Benchmark for learning stiff problems using physics-informed machine learning
  ☆11Updated 3 years ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆54Updated 2 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆21Updated last month
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆45Updated 3 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆29Updated 2 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆52Updated 3 years ago
• elizqian / operator-inference
  ☆10Updated last year
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆49Updated last year
• 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
• briandesilva / discovery-of-physics-from-data
  Code to accompany the paper "Discovery of Physics from Data: Universal Laws and Discrepancies"
  ☆27Updated 4 years ago
• elizabethnewman / hessQuik
  Computing gradients and Hessians of feed-forward networks with GPU acceleration
  ☆18Updated last year