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"
  ☆450Updated 3 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆277Updated 3 years ago
• kpchamp / SindyAutoencoders
  ☆346Updated 3 years ago
• boschresearch / torchphysics
  ☆428Updated 2 months ago
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆218Updated 4 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆394Updated 11 months ago
• NeuroDiffGym / neurodiffeq
  A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, i…
  ☆728Updated last week
• MilesCranmer / symbolic_deep_learning
  Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"
  ☆745Updated last year
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆727Updated last year
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,448Updated 10 months ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆339Updated 3 months ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆104Updated 3 years ago
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆135Updated last year
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆536Updated 2 years ago
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆277Updated 2 years ago
• SJ001 / AI-Feynman
  ☆667Updated 7 months ago
• neuraloperator / graph-pde
  Using graph network to solve PDEs
  ☆372Updated last year
• esa / torchquad
  Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
  ☆198Updated 3 months ago
• pdebench / PDEBench
  PDEBench: An Extensive Benchmark for Scientific Machine Learning
  ☆840Updated last month
• analysiscenter / pydens
  PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
  ☆303Updated last year
• dynamicslab / pysindy
  A package for the sparse identification of nonlinear dynamical systems from data
  ☆1,524Updated last week
• mfinzi / equivariant-MLP
  A library for programmatically generating equivariant layers through constraint solving
  ☆264Updated last year
• tum-pbs / PhiFlow
  A differentiable PDE solving framework for machine learning
  ☆1,562Updated this week
• PredictiveIntelligenceLab / jaxpi
  ☆268Updated last week
• locuslab / lcp-physics
  A differentiable LCP physics engine in PyTorch.
  ☆297Updated 4 years ago
• Zymrael / awesome-neural-ode
  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical…
  ☆1,402Updated 5 months ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆72Updated 2 years ago
• pdearena / pdearena
  ☆246Updated 5 months ago
• patrick-kidger / optimistix
  Nonlinear optimisation (root-finding, least squares, ...) in JAX+Equinox. https://docs.kidger.site/optimistix/
  ☆378Updated last week
• patrick-kidger / diffrax
  Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
  ☆1,548Updated last week