Alternatives and similar repositories for hamiltonian-nn

Users that are interested in hamiltonian-nn are comparing it to the libraries listed below

• MilesCranmer / lagrangian_nns
  Lagrangian Neural Networks
  ☆527Updated 2 months ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆448Updated last year
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆286Updated 4 years ago
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆787Updated last year
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆551Updated 2 years ago
• kpchamp / SindyAutoencoders
  ☆377Updated 4 years ago
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆223Updated 5 years ago
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,540Updated last year
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆767Updated 4 months ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 years ago
• boschresearch / torchphysics
  OSS library that implements deep learning methods for partial differential equations and much more
  ☆455Updated 2 months ago
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,494Updated last year
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆283Updated 3 years ago
• MilesCranmer / symbolic_deep_learning
  Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"
  ☆769Updated 2 years ago
• neuraloperator / graph-pde
  Using graph network to solve PDEs
  ☆421Updated 6 months ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆395Updated last year
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated last week
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆145Updated 2 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆465Updated last year
• google / jax-cfd
  Computational Fluid Dynamics in JAX
  ☆895Updated last month
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆460Updated 3 months ago
• analysiscenter / pydens
  PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
  ☆312Updated last year
• mfinzi / equivariant-MLP
  A library for programmatically generating equivariant layers through constraint solving
  ☆280Updated 2 years ago
• rtqichen / ffjord
  code for "FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models".
  ☆663Updated 5 years ago
• tum-pbs / PhiFlow
  A differentiable PDE solving framework for machine learning
  ☆1,742Updated last month
• PredictiveIntelligenceLab / jaxpi
  ☆380Updated 3 weeks ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆91Updated 3 years ago
• pdebench / PDEBench
  PDEBench: An Extensive Benchmark for Scientific Machine Learning
  ☆1,001Updated 6 months ago
• snagcliffs / PDE-FIND
  ☆271Updated 3 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆153Updated 2 years ago