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
ACID: Action-Conditional Implicit Visual Dynamics for Deformable Object Manipulation
Data-driven reduced order modeling for nonlinear dynamical systems
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
AI4Science: Efficient data-driven Online Model Learning (OML) / system identification and control
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.
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.
Supplementary materials to the lecture data driven audio signal processing
a little library to help me with things involving Koopman operators
Matlab implementation of online and window dynamic mode decomposition algorithms
Sparse Identification of Truncation Errors (SITE) for Data-Driven Discovery of Modified Differential Equations
Constructing linearizing transformations for reduced-order modeling of nonlinear dynamical systems
Fourier Feature Character Animation Controller Demo
PILOTS (ProgrammIng Language for spatiO-Temporal data Streaming applications)
Non-intrusive reduced-order modeling with geometry-informed snapshots. Current based registration is applied to compute the diffeomorphism between snapshots.
Delay Embedded Regressive Reduced Order Model
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