physics-informed-ml
Here are 11 public repositories matching this topic...
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
-
Updated
Feb 20, 2020 - Python
MeshfreeFlowNet: Physical Constrained Space Time Super-Resolution
-
Updated
May 6, 2020 - Python
Deep learning library for solving differential equations and more
-
Updated
Aug 25, 2021 - Python
Deep learning for Engineers - Physics Informed Deep Learning
-
Updated
Sep 9, 2021 - Python
Supporting code for "reduced order modeling using advection-aware autoencoders"
-
Updated
Aug 30, 2022 - Python
Π-ML: Learn data-driven similarity theories of physical problems
-
Updated
Feb 8, 2024 - Python
Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.
-
Updated
Mar 10, 2024 - Python
Includes codes for the forthcoming paper, "Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning"
-
Updated
May 5, 2024 - Python
Learning function operators with neural networks.
-
Updated
Jun 12, 2024 - Python
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
-
Updated
Jun 14, 2024 - Python
Improve this page
Add a description, image, and links to the physics-informed-ml topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the physics-informed-ml topic, visit your repo's landing page and select "manage topics."