Topic: physics-informed Goto Github
Some thing interesting about physics-informed
Some thing interesting about physics-informed
physics-informed,Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs
Organization: cics-nd
Home Page: https://doi.org/10.1016/j.jcp.2019.109056
physics-informed,Going through the tutorial on Physics-informed Neural Networks: https://github.com/madagra/basic-pinn
User: jbris
Home Page: https://jbris.github.io/physics_informed_nn_tutorial/
physics-informed,Research project conducted at Pacific Northwest National Laboratory, exploring the use of physics-informed autoencoders to predict fluid flow dynamics
User: jrice15
physics-informed,Physics-Informed Neural networks for Advanced modeling
Organization: mathlab
Home Page: https://mathlab.github.io/PINA/
physics-informed,TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
User: pierremtb
physics-informed,TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).
User: pierremtb
physics-informed,Physics-informed information field theory - Solve inverse problems with built-in model form uncertainty estimation
Organization: predictivesciencelab
physics-informed,SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
Organization: sciml
Home Page: https://docs.sciml.ai/SciMLBenchmarksOutput/stable/
physics-informed,Code for paper "Physics-based machine learning for modeling IP3 induced calcium oscillations" - DOI: 10.5281/zenodo.4839127
User: smrfeld
physics-informed,UQ Group (Director: Hadi Meidani)
User: uq-group
Home Page: https://uq-group.github.io
physics-informed,Dimensionless learning codes for our paper called "Data-driven discovery of dimensionless numbers and governing laws from scarce measurements".
User: xiaoyuxie-vico
Home Page: https://xiaoyuxie.top/PyDimension-Book/intro.html
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