Alternatives and similar repositories for aTEAM:

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

• sisl / deep_flow_control
  Source code for "Deep Dynamical Modeling and Control of Unsteady Fluid Flows" from NeurIPS 2018
  ☆46Updated 6 years ago
• PredictiveIntelligenceLab / UQPINNs
  ☆62Updated 5 years ago
• PhIMaL / DeePyMoD_torch
  Pytorch implementation of the DeepMoD algorithm: [arXiv:1904.09406]
  ☆32Updated last year
• maziarraissi / MultistepNNs
  Multistep Neural Networks for Data-driven Discovery of Nonlinear Dynamical Systems
  ☆63Updated 5 years ago
• remcovandermeer / Optimally-Weighted-PINNs
  ☆41Updated 4 years ago
• yakovlev31 / graphpdes_experiments
  ☆34Updated 4 years ago
• computational-imaging / GraphPDE
  ☆49Updated 2 years ago
• LeungSamWai / Finite-expression-method
  ☆19Updated 2 years ago
• Zhengyu-Huang / Operator-Learning
  ☆39Updated 2 years ago
• cics-nd / pde-surrogate
  Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
  ☆145Updated 5 years ago
• amkatrutsa / DeepPDE
  Deep Learning application to the partial differential equations
  ☆30Updated 6 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
• maziarraissi / NumericalGP
  Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
  ☆67Updated 4 years ago
• dbgannon / NNets-and-Diffeqns
  jupyter notebooks for the neural nets and differential equation paper
  ☆28Updated 3 years ago
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated last year
• cics-nd / ar-pde-cnn
  Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
  ☆92Updated 2 years ago
• cics-nd / cnn-surrogate
  Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
  ☆106Updated 4 years ago
• snagcliffs / parametric-discovery
  ☆24Updated 6 years ago
• atzberg / gmls-nets
  PyTorch implementation of GMLS-Nets. Machine learning methods for scattered unstructured data sets. Methods for learning differential op…
  ☆26Updated last year
• 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
• ShashankSubramanian / neuraloperators-TL-scaling
  Code for Characterizing Scaling and Transfer Learning Behavior of FNO in SciML
  ☆42Updated last year
• locuslab / cfd-gcn
  ☆120Updated last year
• yufeiwang63 / L2D-learning-to-discretize
  source code of learning to discretize solving 1d scalar conservation laws via deep reinforcement learning
  ☆15Updated 4 years ago
• peterparity / symder
  SymDer: Symbolic Derivative Approach to Discovering Sparse Interpretable Dynamics from Partial Observations
  ☆20Updated 2 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆25Updated 3 years ago
• PhIMaL / DeePyMoD
  ☆47Updated last year
• lu-group / deeponet-extrapolation
  DeepONet extrapolation
  ☆26Updated last year
• rmojgani / PhysicsAwareAE
  The unsupervised learning problem trains a diffeomorphic spatio-temporal grid, that registers the output sequence of the PDEs onto a non-…
  ☆19Updated 2 years ago
• Rose-STL-Lab / Turbulent-Flow-Net
  Turbulent flow network source code
  ☆66Updated last week
• MariusZeinhofer / Natural-Gradient-PINNs-ICML23
  This is the repository for the code used in the ICML23 paper called "Achieving High Accuracy with PINNs via Energy Natural Gradient Desce…
  ☆17Updated 4 months ago