Alternatives and similar repositories for weakformghnn:

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

• zhengdao-chen / SRNN
  Symplectic Recurrent Neural Networks
  ☆27Updated 2 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆39Updated 3 years ago
• IdahoLabResearch / BIhNNs
  The code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural …
  ☆14Updated 2 years ago
• lorenzrichter / PDE-backward-solver
  ☆20Updated 4 months ago
• cagatayyildiz / npde
  Nonparametric Differential Equation Modeling
  ☆53Updated 11 months ago
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆49Updated 2 years ago
• Zymrael / PortHamiltonianNN
  Port-Hamiltonian Approach to Neural Network Training
  ☆22Updated 5 years ago
• PredictiveIntelligenceLab / GP-NODEs
  ☆28Updated 2 years ago
• jpzxshi / sympnets
  ☆26Updated 3 years ago
• mfinzi / constrained-hamiltonian-neural-networks
  ☆104Updated 3 years ago
• yuan-yin / APHYNITY
  Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting
  ☆42Updated last year
• PredictiveIntelligenceLab / NOMAD
  ☆15Updated 6 months ago
• neuraloperator / markov_neural_operator
  ☆28Updated 8 months ago
• brandstetter-johannes / LPSDA
  Repo to the paper "Lie Point Symmetry Data Augmentation for Neural PDE Solvers"
  ☆49Updated last year
• 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…
  ☆19Updated last year
• cselab / LED
  ☆19Updated 2 years ago
• astanziola / fourier-neural-operator-flax
  An unofficial implementation of the Fourier Neural Operator in Flax
  ☆17Updated 8 months ago
• DesmondZhong / Lagrangian_caVAE
  Official implementation for our paper "Unsupervised Learning of Lagrangian Dynamics from Images for Prediction and Control"
  ☆18Updated 2 years ago
• peterparity / symder
  SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
  ☆18Updated 2 years ago
• MatthieuDarcy / KernelsOperatorLearning
  ☆10Updated 2 months ago
• Physics-aware-AI / Symplectic-ODENet
  ☆45Updated 4 years ago
• martenlienen / finite-element-networks
  Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations wi…
  ☆70Updated 9 months ago
• Zhengyu-Huang / Operator-Learning
  ☆37Updated 2 years ago
• d-biswa / Symplectic-ODENet
  ☆15Updated 4 years ago
• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆39Updated 4 years ago
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 4 years ago
• yuan-yin / CoDA
  Generalizing to New Physical Systems via Context-Informed Dynamics Model
  ☆22Updated 9 months ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆86Updated 2 years ago
• tomoleary / dino
  Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning
  ☆17Updated last year
• remcovandermeer / Optimally-Weighted-PINNs
  ☆41Updated 4 years ago