Alternatives and similar repositories for NNets-and-Diffeqns

Users that are interested in NNets-and-Diffeqns are comparing it to the libraries listed below

• ZichaoLong / aTEAM
  A pyTorch Extension for Applied Mathematics
  ☆39Updated 5 years ago
• cics-nd / pde-surrogate
  Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
  ☆148Updated 5 years ago
• biomathlab / PDElearning
  Code repository for the paper "Learning partial differential equations for biological transport models from noisy spatiotemporal data"
  ☆10Updated 6 years ago
• PredictiveIntelligenceLab / UQPINNs
  ☆63Updated 5 years ago
• PredictiveIntelligenceLab / USNCCM15-Short-Course-Recent-Advances-in-Physics-Informed-Deep-Learning
  ☆116Updated 5 years ago
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• luckystarufo / multiscale_HiTS
  ☆72Updated 4 years ago
• remcovandermeer / Optimally-Weighted-PINNs
  ☆41Updated 5 years ago
• pswpswpsw / paper-nif
  ☆38Updated last year
• sisl / deep_flow_control
  Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
  ☆49Updated 6 years ago
• cics-nd / cnn-surrogate
  Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
  ☆106Updated 4 years ago
• fsahli / EikonalNet
  ☆20Updated 5 years ago
• tensordiffeq / TensorDiffEq
  Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed c…
  ☆114Updated 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
• maziarraissi / DeepHPMs
  Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations
  ☆279Updated 2 years ago
• locuslab / cfd-gcn
  ☆125Updated 2 years ago
• pswpswpsw / nif
  A library for dimensionality reduction on spatial-temporal PDE
  ☆66Updated last year
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated last year
• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆32Updated last year
• maziarraissi / HPM
  Hidden physics models: Machine learning of nonlinear partial differential equations
  ☆145Updated 5 years ago
• maziarraissi / FBSNNs
  Forward-Backward Stochastic Neural Networks: Deep Learning of High-dimensional Partial Differential Equations
  ☆154Updated 5 years ago
• pswpswpsw / SKDMD
  Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
  ☆30Updated 2 years ago
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆69Updated 5 years ago
• PhIMaL / DeePyMoD
  ☆48Updated last year
• amkatrutsa / DeepPDE
  Deep Learning application to the partial differential equations
  ☆30Updated 7 years ago
• PredictiveIntelligenceLab / TRIPODS_Winter_School_2022
  Practicum on Supervised Learning in Function Spaces
  ☆33Updated 3 years ago
• dynamicslab / dominant-balance
  Methods and code for J. L. Callaham, J. N. Kutz, B. W. Brunton, and S. L. Brunton (2020)
  ☆57Updated 4 years ago
• maziarraissi / PDE_GP
  Machine learning of linear differential equations using Gaussian processes
  ☆24Updated 7 years ago
• neuraloperator / markov_neural_operator
  ☆35Updated last year
• jayroxis / qres
  Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)
  ☆16Updated 4 years ago