PDE-Net: Learning PDEs from Data
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Updated
Jun 26, 2021
PDE-Net: Learning PDEs from Data
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
Creating animation sequences between sparse key frames using motion phase features.
Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
Data-driven reduced order modeling for nonlinear dynamical systems
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
AI4Science: Python/Matlab implementation of online and window dynamic mode decomposition (Online DMD and Window DMD)
Python-based object-oriented discrete-event simulation tool for complex, data-driven modeling
Source code for the paper "Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process" by S. A. McQuarrie, C. Huang, and K. E. Willcox.
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
Awesome-spatial-temporal-data-mining-packages. Julia and Python resources on spatial and temporal data mining. Mathematical epidemiology as an application. Most about package information. Data Sources Links and Epidemic Repos are also included. Keep updating.
[CVPR 2025] Pytorch implementation of the paper "Hearing Anywhere in Any Environment"
Supplementary materials to the lecture data driven audio signal processing
This approach is used to solve data-driven optimal control problems by providing a Koopman operator based convex formulation
A distributed hydrology-guided neural network model for streamflow prediction
Matlab implementation of online and window dynamic mode decomposition algorithms
a little library to help me with things involving Koopman operators
Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems
Sparse Identification of Truncation Errors (SITE) for Data-Driven Discovery of Modified Differential Equations
Fourier Feature Character Animation Controller Demo
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