Alternatives and similar repositories for weakformghnn

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

• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆48Updated 2 years ago
• Physics-aware-AI / Symplectic-ODENet
  ☆47Updated 5 years ago
• cselab / LED
  ☆21Updated 3 years ago
• peterparity / symder
  SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
  ☆24Updated 3 years ago
• gaurav71531 / mwt-operator
  Multiwavelets-based operator model
  ☆69Updated 3 years ago
• Zymrael / PortHamiltonianNN
  Port-Hamiltonian Approach to Neural Network Training
  ☆27Updated 6 years ago
• peterparity / PDE-VAE-pytorch
  PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
  ☆36Updated 4 years ago
• lukebhan / PDEControlGym
  This gym provides implementations of various PDEs for easy testing and comparison of data-driven and classical PDE control algorithms.
  ☆39Updated last month
• jpzxshi / sympnets
  ☆31Updated last month
• sisl / deep_flow_control
  Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
  ☆49Updated 7 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆42Updated 4 years ago
• jpzxshi / learner
  ☆23Updated 7 months ago
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆54Updated 3 years ago
• NBoulle / RationalNets
  Code for the paper "Rational neural networks", NeurIPS 2020
  ☆29Updated 4 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆112Updated 4 years ago
• AI4Science-WestlakeU / le-pde-uq
  [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both…
  ☆16Updated last year
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆61Updated 3 years ago
• yakovlev31 / graphpdes_experiments
  ☆35Updated 5 years ago
• roxie62 / neural_operators_for_chaos
  ☆13Updated 11 months ago
• erichson / koopmanAE
  Consistent Koopman Autoencoders
  ☆75Updated 2 years ago
• VLSF / SNO
  Spectral Neural Operator
  ☆79Updated 2 years ago
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆29Updated 8 months ago
• neuraloperator / markov_neural_operator
  ☆41Updated 5 months ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆92Updated 3 years ago
• asikist / nnc
  A framework for neural network control of dynamical systems over graphs.
  ☆57Updated 3 years ago
• PhIMaL / DeePyMoD
  ☆50Updated 2 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 3 years ago
• sungyongs / dpgn
  Differentiable Physics-informed Graph Networks
  ☆67Updated 5 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 5 years 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