Alternatives and similar repositories for Gaussian-Process-Slover-for-High-Freq-PDE

Users that are interested in Gaussian-Process-Slover-for-High-Freq-PDE are comparing it to the libraries listed below

• tonyzyl / DiffusionReconstruct
  Benchmarking of diffusion models for global field reconstruction from sparse observations
  ☆23Updated 8 months ago
• csccm-iitd / VB-DeepONet
  ☆12Updated 2 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆27Updated 3 years ago
• Blue-Giant / FMPINN
  Solving a class of elliptic partial differential equations(PDEs) with multiple scales utilizing Fourier-based mixed physics informed neur…
  ☆12Updated last year
• delta-lab-ai / pde-controller
  ☆21Updated 2 months ago
• zhaoxiaoyu1995 / RecFNO
  This is the implementation of the RecFNO.
  ☆21Updated 2 years ago
• JohnCSu / DeepONet_Pytorch_Demo
  Simple demo on implementing data driven and physics informed Deep O Nets in pytorch
  ☆15Updated last year
• SuihongSong / Physics-informed_multi-grid_neural_operator
  ☆22Updated last year
• PredictiveIntelligenceLab / UQDeepONet
  ☆10Updated 2 years ago
• ASK-Berkeley / physics-NNs-hard-constraints
  [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.
  ☆34Updated last year
• TapasTripura / WNO
  Wavelet Neural Operator for solving parametric partialdifferential equations in computational mechanics problems
  ☆42Updated last week
• vivekoommen / NeuralOperator_DiffusionModel
  ☆45Updated 5 months ago
• ningliu-iga / DAFNO
  Domain Agnostic Fourier Neural Operators (DAFNO)
  ☆15Updated 11 months ago
• Sysuzqs / DFVM
  Deep finite volume method
  ☆22Updated last year
• HewlettPackard / separable-operator-networks
  Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
  ☆28Updated 9 months ago
• csccm-iitd / WNO
  ☆58Updated last week
• tianshao1992 / DENO4pytorch
  Differential equation neural operator
  ☆23Updated last year
• cselab / G-LED
  Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems
  ☆35Updated 5 months ago
• JacobSRPage / super-res-dynamical
  ☆11Updated 8 months ago
• vivekoommen / NPJCOMPUMATS-03747
  Learning two-phase microstructure evolution using neural operators and autoencoder architectures
  ☆25Updated last year
• zheyuanhu01 / SDGD_PINN
  Tackling the Curse of Dimensionality with Physics-Informed Neural Networks
  ☆14Updated last year
• zheyuanhu01 / AugmentedPINN
  Code accompanying the manuscript "Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition m…
  ☆15Updated last year
• geekyifei / randomized-PINN
  Implementations of the "randomize-then-optimize" approach for sampling Bayesian Physics-informed Neural Network posteriors
  ☆10Updated 4 months ago
• camlab-ethz / DSE-for-NeuralOperators
  Code for "Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains"
  ☆22Updated last year
• apivich-h / pinnacle
  🏔️ PINNACLE: PINN Adaptive ColLocation and Experimental points selection
  ☆22Updated last year
• zhijie-group / Orthogonal-Neural-operator
  Code for orthogonal neural operator
  ☆17Updated last year
• lu-group / deeponet-extrapolation
  Reliable extrapolation of deep neural operators informed by physics or sparse observations
  ☆27Updated 2 years ago
• AI4Science-WestlakeU / beno
  [ICLR24] A boundary-embedded neural operator that incorporates complex boundary shape and inhomogeneous boundary values
  ☆29Updated 8 months ago
• PredictiveIntelligenceLab / LOCA
  ☆15Updated last year
• bilzinet / pifno
  Physics Informed Fourier Neural Operator
  ☆24Updated 9 months ago