Alternatives and similar repositories for Hard_constraint_projection_HCP:

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

• katiana22 / TL-DeepONet
  Source code of 'Deep transfer operator learning for partial differential equations under conditional shift'.
  ☆69Updated last year
• isds-neu / PhyCRNet
  Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
  ☆147Updated 10 months ago
• obok13 / B-PINNs
  Pytorch implementation of Bayesian physics-informed neural networks
  ☆55Updated 3 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆25Updated 3 years ago
• zhry10 / PhyLSTM
  We introduce an innovative physics-informed LSTM framework for metamodeling of nonlinear structural systems with scarce data.
  ☆78Updated last year
• lu-group / gpinn
  gPINN: Gradient-enhanced physics-informed neural networks
  ☆84Updated 2 years ago
• nn4pde / SPINN
  Sparse Physics-based and Interpretable Neural Networks
  ☆47Updated 3 years ago
• mroberto166 / nio
  ☆31Updated last year
• Raocp / PeRCNN
  Physics-encoded recurrent convolutional neural network
  ☆45Updated 3 years ago
• PredictiveIntelligenceLab / MultiscalePINNs
  ☆130Updated 2 years ago
• lululxvi / hpinn
  hPINN: Physics-informed neural networks with hard constraints
  ☆126Updated 3 years ago
• MinglangYin / PyTorchTutorial
  Examplary code for NN, MFNN, DynNet, PINNs and CNN
  ☆49Updated 3 years ago
• ehsankharazmi / hp-VPINNs
  hp-VPINNs: variational physics-informed neural network with domain decomposition is a general framework to solve differential equations
  ☆76Updated 2 years ago
• katiana22 / latent-deeponet
  Source code of "Learning nonlinear operators in latent spaces for real-time predictions of complex dynamics in physical systems."
  ☆58Updated 8 months ago
• bilzinet / pifno
  Physics Informed Fourier Neural Operator
  ☆19Updated 4 months ago
• junbinhuang / DeepRitz
  Implementation of the Deep Ritz method and the Deep Galerkin method
  ☆53Updated 4 years ago
• Jianxun-Wang / Physics-constrained-Bayesian-deep-learning
  Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data
  ☆48Updated 4 years ago
• lu-group / pinn-sampling
  Non-adaptive and residual-based adaptive sampling for PINNs
  ☆67Updated 2 years ago
• csccm-iitd / WNO
  ☆47Updated 2 months ago
• liuxu97531 / PINN_TFI-HSS
  The code for the paper Temperature field inversion of heat-source systems via physics-informed neural networks
  ☆32Updated 2 years ago
• menggedu / DISCOVER
  Deep identification of symbolic open-form PDEs via enhanced reinforcement-learning
  ☆33Updated 3 months ago
• paulpuren / PhyCRNet
  Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs
  ☆31Updated 3 years ago
• hojunkim13 / PINNs
  Basic implementation of physics-informed neural network with pytorch.
  ☆64Updated 2 years ago
• zwqwo / PINN_scratch
  ☆61Updated 2 years ago
• AdityaLab / pinnsformer
  ☆118Updated 5 months ago
• isds-neu / EQDiscovery
  Physics-informed learning of governing equations from scarce data
  ☆137Updated last year
• chiuph / CAN-PINN
  Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
  ☆26Updated last year
• PredictiveIntelligenceLab / Long-time-Integration-PI-DeepONets
  ☆53Updated 2 years ago
• KTH-FlowAI / beta-Variational-autoencoders-and-transformers-for-reduced-order-modelling-of-fluid-flows
  ☆30Updated last year
• soanagno / rba-pinns
  Original implementation of fast PINN optimization with RBA weights
  ☆49Updated 5 months ago