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"
  ☆499Updated 4 years ago
• kpchamp / SindyAutoencoders
  ☆377Updated 4 years ago
• BethanyL / DeepKoopman
  neural networks to learn Koopman eigenfunctions
  ☆460Updated last year
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆287Updated 4 years ago
• dynamicslab / pykoopman
  A package for computing data-driven approximations to the Koopman operator.
  ☆401Updated last year
• boschresearch / torchphysics
  OSS library that implements deep learning methods for partial differential equations and much more
  ☆456Updated 3 months ago
• titu1994 / tfdiffeq
  Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
  ☆223Updated 5 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 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…
  ☆770Updated 5 months ago
• SJ001 / AI-Feynman
  ☆733Updated last year
• MilesCranmer / symbolic_deep_learning
  Code for "Discovering Symbolic Models from Deep Learning with Inductive Biases"
  ☆771Updated 2 years ago
• zabaras / transformer-physx
  Transformers for modeling physical systems
  ☆145Updated 2 years ago
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆159Updated 4 years ago
• EmilienDupont / augmented-neural-odes
  Pytorch implementation of Augmented Neural ODEs
  ☆553Updated 2 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆79Updated 3 years ago
• DiffEqML / torchdyn
  A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
  ☆1,549Updated last year
• esa / torchquad
  Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX
  ☆211Updated 5 months ago
• msurtsukov / neural-ode
  Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
  ☆791Updated last year
• pnnl / neuromancer
  Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric …
  ☆1,254Updated last month
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆65Updated 2 weeks ago
• william-redman / Koopman-Neural-Network-Training
  Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theo…
  ☆21Updated 2 years ago
• google / jax-cfd
  Computational Fluid Dynamics in JAX
  ☆905Updated last month
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆284Updated 3 years ago
• snagcliffs / PDE-FIND
  ☆274Updated 3 years ago
• martius-lab / EQL
  Equation Learner, a neural network approach to symbolic regression
  ☆84Updated last year
• GilpinLab / dysts
  Hundreds of strange attractors
  ☆512Updated last week
• BoyuanChen / neural-state-variables
  ☆178Updated 3 years ago
• analysiscenter / pydens
  PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
  ☆312Updated last year
• helange23 / from_fourier_to_koopman
  Linear and non-linear spectral forecasting algorithms
  ☆139Updated 4 years ago
• probabilistic-numerics / probnum
  Probabilistic Numerics in Python.
  ☆458Updated 6 months ago