Alternatives and similar repositories for lagrangian_nns:

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

• greydanus / hamiltonian-nn
  Code for our paper "Hamiltonian Neural Networks"
  ☆467Updated 4 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆278Updated 3 years ago
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆740Updated 2 months ago
• boschresearch / torchphysics
  ☆434Updated 4 months ago
• kpchamp / SindyAutoencoders
  ☆352Updated 3 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆107Updated 3 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆406Updated last year
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆218Updated 4 years ago
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆136Updated last year
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆348Updated 5 months ago
• MilesCranmer / symbolic_deep_learning
  Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"
  ☆749Updated last year
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,469Updated 11 months ago
• neuraloperator / graph-pde
  Using graph network to solve PDEs
  ☆382Updated last year
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,424Updated 7 months ago
• mathLab / PINA
  Physics-Informed Neural networks for Advanced modeling
  ☆481Updated this week
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆541Updated 2 years ago
• pdebench / PDEBench
  PDEBench: An Extensive Benchmark for Scientific Machine Learning
  ☆879Updated 2 months ago
• google / jax-cfd
  Computational Fluid Dynamics in JAX
  ☆821Updated 3 weeks ago
• snagcliffs / PDE-FIND
  ☆249Updated 2 years ago
• analysiscenter / pydens
  PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
  ☆307Updated last year
• pdearena / pdearena
  ☆253Updated 7 months ago
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆279Updated 2 years ago
• PredictiveIntelligenceLab / jaxpi
  ☆295Updated last month
• mfinzi / equivariant-MLP
  A library for programmatically generating equivariant layers through constraint solving
  ☆267Updated last year
• SJ001 / AI-Feynman
  ☆681Updated 9 months ago
• tum-pbs / PhiFlow
  A differentiable PDE solving framework for machine learning
  ☆1,591Updated last week
• tumaer / JAXFLUIDS
  Differentiable Fluid Dynamics Package
  ☆396Updated this week
• Photon-AI-Research / NeuralSolvers
  Neural network based solvers for partial differential equations and inverse problems . Implementation of physics-informed neural networks…
  ☆149Updated 3 months ago
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,597Updated last week
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆745Updated last year