Alternatives and similar repositories for inn-surrogate

Users that are interested in inn-surrogate are comparing it to the libraries listed below

• pkmtum / Semi-supervised_Invertible_Neural_Operators
  Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems
  ☆13Updated last year
• VincLee8188 / Physics-Informed-Neural-Networks-PyTorch
  Implementation of physics informed neural networks with PyTorch
  ☆20Updated 4 years ago
• JALB-epsilon / Fine-tuning-NOs
  ☆14Updated last year
• mroberto166 / nio
  ☆32Updated last year
• Zhengyu-Huang / Operator-Learning
  ☆41Updated 2 years ago
• PredictiveIntelligenceLab / TRIPODS_Winter_School_2022
  Practicum on Supervised Learning in Function Spaces
  ☆33Updated 3 years ago
• arkadaw9 / PID-GAN
  ☆20Updated 3 years ago
• wavebench / wavebench
  ☆12Updated last year
• weipengOO98 / rang_pinn
  Code for reproducing the paper: RANG: A Residual-based Adaptive Node Generation Method for Physics-Informed Neural Networks
  ☆15Updated 3 years ago
• scaomath / eit-transformer
  [ICLR 2023] Interplay between the Attention and Electrical Impedance Tomography
  ☆34Updated 2 years ago
• kkothari93 / fionet
  Official repo for "Learning the geometry of wave-based imaging"
  ☆12Updated 4 years ago
• vivekoommen / NPJCOMPUMATS-03747
  Learning two-phase microstructure evolution using neural operators and autoencoder architectures
  ☆23Updated last year
• AmeyaJagtap / Locally-Adaptive-Activation-Functions-Neural-Networks-
  Python codes for Locally Adaptive Activation Function (LAAF) used in deep neural networks. Please cite this work as "A D Jagtap, K Kawa…
  ☆40Updated 2 years ago
• bsciolla / gaussian-random-fields
  Generator of 2D gaussian random fields
  ☆50Updated 3 years ago
• HewlettPackard / separable-operator-networks
  Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
  ☆26Updated 7 months ago
• nn4pde / SPINN
  Sparse Physics-based and Interpretable Neural Networks
  ☆50Updated 3 years ago
• zhaoxiaoyu1995 / RecFNO
  This is the implementation of the RecFNO.
  ☆20Updated 2 years ago
• jcallaham / robust-flow-reconstruction
  Code for "Robust flow field reconstruction from limited measurements vis sparse representation" (J. Callaham, K. Maeda, and S. Brunton 20…
  ☆14Updated 6 years ago
• peterparity / PDE-VAE-pytorch
  PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
  ☆35Updated 3 years ago
• RizaXudayi / VarNet
  Variational Neural Networks for the Solution of Partial Differential Equations
  ☆8Updated 5 years ago
• chiuph / CAN-PINN
  Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
  ☆28Updated last year
• Duke-MG-Lab / Allen-Cahn-FNO
  Fourier Neural Operators to solve for Allen Cahn PDE equations
  ☆18Updated 3 years ago
• pswpswpsw / paper-nif
  ☆38Updated last year
• vivekoommen / NeuralOperator_DiffusionModel
  ☆36Updated 2 months ago
• ashiq24 / UNO
  ☆59Updated 2 months ago
• hippylib / hippyflow
  Dimension reduced surrogate construction for parametric PDE maps
  ☆37Updated 2 months ago
• PredictiveIntelligenceLab / PDE-constrained-optimization-PI-DeepONet
  ☆14Updated 3 years ago
• vislearn / analyzing_inverse_problems
  Code for the paper "Analyzing inverse problems with invertible neural networks." (2018)
  ☆95Updated 5 years ago
• PredictiveIntelligenceLab / Long-time-Integration-PI-DeepONets
  ☆53Updated 2 years ago
• cselab / odil
  ODIL (Optimizing a Discrete Loss) is a Python framework for solving inverse and data assimilation problems for partial differential equat…
  ☆105Updated last month