Alternatives and similar repositories for phygnn

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

• gmisy / Physics-Informed-Neural-Networks-for-Power-Systems
  ☆91Updated 5 years ago
• dynamicslab / pysensors
  PySensors is a Python package for sparse sensor placement
  ☆91Updated last month
• GargyaGokhale / PhysNet_Thermal_Models
  Physics informed neural networks for control-oriented building thermal models
  ☆28Updated 3 years ago
• Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
  Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
  ☆49Updated 4 years ago
• PML-UCF / pinn_ode_tutorial
  ☆124Updated 2 years ago
• Crunch-UQ4MI / neuraluq
  ☆180Updated 2 months ago
• dynamicslab / modified-SINDy
  Example code for paper: Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributio…
  ☆55Updated 3 years ago
• arkadaw9 / PGNN
  Physics-guided Neural Networks (PGNN) : An Application In Lake Temperature Modelling
  ☆109Updated 3 years ago
• PredictiveIntelligenceLab / USNCCM15-Short-Course-Recent-Advances-in-Physics-Informed-Deep-Learning
  ☆117Updated 5 years ago
• PredictiveIntelligenceLab / BayesianDifferentiableProgramming
  ☆21Updated 4 years ago
• clegaard / deep_learning_for_dynamical_systems
  ☆87Updated 2 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆26Updated 3 years ago
• hippylib / soupy
  Stochastic Optimization under Uncertainty in Python.
  ☆36Updated last week
• jkneifl / VENI-VINDy-VICI
  An interpretable data-driven framework for building generative reduced order models with embedded uncertainty quantification
  ☆32Updated 3 months ago
• PML-UCF / pinn
  Physics-informed neural networks package
  ☆308Updated 2 years ago
• DENG-MIT / Stiff-PINN
  Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical Kinetics
  ☆59Updated 3 years ago
• isds-neu / EQDiscovery
  Physics-informed learning of governing equations from scarce data
  ☆144Updated last year
• shaandesai1 / TransferDE
  One-Shot Transfer Learning of PINNs
  ☆11Updated last year
• katiana22 / GDM-PCE
  Source code of: "Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models".
  ☆37Updated 2 years ago
• luckystarufo / pySINDy
  SINDy (Sparse Identification of Nonlinear Dynamics) algorithms
  ☆74Updated 2 years ago
• VVeida / RK4_PINN
  ☆11Updated last year
• rmojgani / LPINNs
  To address some of the failure modes in training of physics informed neural networks, a Lagrangian architecture is designed to conform to…
  ☆49Updated 2 years ago
• soanagno / wakenet
  Offshore wind farm wake modelling using deep feed forward neural networks for active yaw control and layout optimisation
  ☆37Updated last year
• ZhaoChenCivilSciML / EQDiscovery-1
  Physics-informed learning of governing equations from scarce data
  ☆11Updated 4 years ago
• LLNL / GPLaSDI
  ☆34Updated last month
• TheodoreWolf / pinns
  Playing around with Phyiscs-Informed Neural Networks
  ☆79Updated last month
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• quercushernandez / ThermodynamicsGNN
  Code for the paper "Thermodynamics-informed graph neural networks" published in IEEE Transactions on Artificial Intelligence (TAI).
  ☆100Updated 9 months ago
• jbesty / PINN_system_identification
  ☆32Updated 2 years ago
• NREL / WPGNN
  ☆20Updated last month