Alternatives and similar repositories for Bayesian-PINN-Pytorch

Users that are interested in Bayesian-PINN-Pytorch are comparing it to the libraries listed below

• csccm-iitd / VB-DeepONet
  ☆12Updated 2 years ago
• jayroxis / qres
  Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)
  ☆16Updated 4 years ago
• mroberto166 / nio
  ☆33Updated last year
• AI4Science-WestlakeU / le-pde-uq
  [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both…
  ☆16Updated last year
• LivingMatterLab / xPINNs
  when using, please cite "Bayesian Physics-Informed Neural Networks for real-world nonlinear dynamical systems", CMAME, https://doi.org/1…
  ☆70Updated 2 years ago
• sethhirsh / BayesianSindy
  ☆14Updated 3 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆26Updated 3 years ago
• CognitiveModeling / finn
  The public repository about our joint FINN research project
  ☆36Updated 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."
  ☆62Updated 2 months ago
• ShuaiGuo16 / PI-DeepONet
  Implementing a physics-informed DeepONet from scratch
  ☆42Updated last year
• pkmtum / Semi-supervised_Invertible_Neural_Operators
  Semi-supervised Invertible Neural Operators for Bayesian Inverse Problems
  ☆13Updated last year
• xuangu-fang / Gaussian-Process-Slover-for-High-Freq-PDE
  Solving High Frequency and Multi-Scale PDEs with Gaussian Processes (ICLR 2024)
  ☆20Updated last year
• PredictiveScienceLab / variational-elliptic-SPDE
  ☆13Updated 5 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
• giuliamesc / BPINNs
  ☆30Updated 2 years ago
• ixScience / fourier_neural_operator
  Use Fourier transform to learn operators in differential equations.
  ☆12Updated 2 years ago
• obok13 / B-PINNs
  Pytorch implementation of Bayesian physics-informed neural networks
  ☆59Updated 3 years ago
• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆30Updated 4 years ago
• bilzinet / pifno
  Physics Informed Fourier Neural Operator
  ☆22Updated 7 months ago
• JRice15 / physics-informed-autoencoders
  Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid …
  ☆35Updated 2 years ago
• peterparity / PDE-VAE-pytorch
  PDE-VAE: Variational Autoencoder for Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning
  ☆36Updated 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
• dmusekamp / al4pde
  AL4PDE: A Benchmark for Active Learning for Neural PDE Solvers
  ☆25Updated 3 weeks ago
• cselab / LED
  ☆21Updated 2 years ago
• chiuph / CAN-PINN
  Coupled-Automatic-Numerical differentiation scheme for physics-informed neural network (can-PINN)
  ☆28Updated last year
• cselab / G-LED
  Generative Learning for Forecasting the Dynamics of High Dimensional Complex Systems
  ☆31Updated 3 months ago
• PredictiveIntelligenceLab / TRIPODS_Winter_School_2022
  Practicum on Supervised Learning in Function Spaces
  ☆33Updated 3 years ago
• PredictiveIntelligenceLab / UQDeepONet
  ☆10Updated 2 years ago
• josephbakarji / deep-delay-autoencoder
  Discovers high dimensional models from 1D data using deep delay autoencoders
  ☆34Updated 2 years ago
• Zhengyu-Huang / Operator-Learning
  ☆41Updated 2 years ago