Alternatives and similar repositories for NeuralDAEs

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

• hippylib / soupy
  Stochastic Optimization under Uncertainty in Python.
  ☆36Updated 5 months ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆59Updated 3 years ago
• sklus / d3s
  Data-driven dynamical systems toolbox.
  ☆77Updated last week
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• MIT-Lu-Lab / MPAX
  Mathematical Programming in JAX
  ☆108Updated 4 months ago
• TUM-ITR / koopcore
  Koopman Kernels for Learning Dynamical Systems from Trajectory Data
  ☆31Updated last year
• qiauil / torchfsm
  TorchFSM: Fourier Spectral Method with PyTorch
  ☆50Updated last week
• Machine-Learning-Dynamical-Systems / kooplearn
  A Python package to learn the Koopman operator.
  ☆63Updated this week
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆56Updated 3 years ago
• yzshi5 / OpFlow
  code for "Universal Functional Regression with Neural Operator Flows" TMLR 2024
  ☆18Updated 4 months ago
• IlyaOrson / Control-NeuralODE
  Neural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248
  ☆18Updated 2 years ago
• DS-4-DS / DS4DS_Course
  Data Science for Dynamical System Course
  ☆129Updated this week
• drgona / PIML_ACC2023
  Material for the tutorial on "Physics-Informed Machine Learning (PIML) for Modeling and Control of Dynamical Systems" presented at the Am…
  ☆19Updated last year
• decargroup / pykoop
  Koopman operator identification library in Python, compatible with `scikit-learn`
  ☆95Updated last month
• jejjohnson / uncertain_gps
  Exploring how to to deal with uncertain inputs with gaussian process regression models.
  ☆27Updated 4 years ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆55Updated last year
• GaloisInc / dlkoopman
  A general-purpose Python package for Koopman theory using deep learning.
  ☆110Updated last month
• dynamicslab / hydrogym
  An RL-Gym for Challenge Problems in Data-Driven Modeling and Control of Fluid Dynamics.
  ☆81Updated 3 months ago
• clegaard / deep_learning_for_dynamical_systems
  ☆89Updated 2 years ago
• cagatayyildiz / npode
  Learning unknown ODE models with Gaussian processes
  ☆26Updated 7 years ago
• ContiPaolo / EKF-SINDy
  Empowering extended Kalman filter (EKF) with Sparse Identification of Nonlinear Dynamics (SINDy)
  ☆64Updated 6 months ago
• DiffEqML / torchcontrol
  A PyTorch library for all things nonlinear control and reinforcement learning.
  ☆47Updated 4 years ago
• andreikitaitsev / SymINDy
  Symbolic Identification of Non-linear Dynamics. The method generalizes the SINDy algorithm by combining sparse and genetic-programming-ba…
  ☆78Updated 3 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆29Updated 4 months ago
• hegdepashupati / gaussian-process-odes
  Implementation of the work Variational multiple shooting for Bayesian ODEs with Gaussian processes
  ☆13Updated 3 years ago
• erichanslee / GP_Derivatives
  Scalable Gaussian Process Regression with Derivatives
  ☆38Updated 6 years ago
• stellatogrp / lropt
  ☆23Updated 4 months ago
• dynamicslab / SINDy-PI
  SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics
  ☆153Updated 4 years ago
• MaximilianB2 / pc-gym
  Reinforcement learning environments for process control applications.
  ☆65Updated last week
• plugyawn / gp-zoo
  A repository with implementations of major papers on Gaussian Process regression models, implemented from scratch in Python, notably incl…
  ☆14Updated 2 years ago