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An attempt to model time series dynamics of biochemical networks using Extended Dynamic Mode Decomposition with tuneable parameters.
Extended dynamic mode decomposition with python
Extended Dynamic Mode Decomposition for system identification from time series data (with dictionary learning, control and streaming options). Diffusion Maps to extract geometric description from d…
Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
Matlab implementation of online and window dynamic mode decomposition algorithms
haozhg / dmdtools
Forked from cwrowley/dmdtoolsA library of tools for computing variants of Dynamic Mode Decomposition
8000 Koopman Reduced-Order Nonlinear Identification and Control
The code used to generate all the plots for the SAM and KASAM (Kolmogorov-Arnold Spline Additive Model/TraumTensor) paper based on work done in 2021.
Aeroelastic Reduced Order Model creation library for CFD aerodynamics
A comprehensive collection of KAN(Kolmogorov-Arnold Network)-related resources, including libraries, projects, tutorials, papers, and more, for researchers and developers in the Kolmogorov-Arnold N…
AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.
Sparsity-Promoting Dynamic Mode Decomposition with Control
Sparsity-promoting Kernel Dynamic Mode Decomposition for Nonlinear Dynamical Systems
Applies the SINDy algorithm (Brunton et. al., 2016) to epidemiological models and data.
MATLAB codes for physics-informed dynamic mode decomposition (piDMD)
Plotting pressure data and transforming into the frequency domain using a FFT for standard Keller pressure transducers
Open source python workflow to segment multiphase flow images
DMD for 4D saturation data
mathLab / PyDMD
67E2 Forked from PyDMD/PyDMDmathLab mirror of Python Dynamic Mode Decomposition
Data-Driven Flow-Map Models for Data-Efficient Discovery of Dynamics and Fast Uncertainty Quantification of Biological and Biochemical Systems
Pytorch implementation of Resnet for time-series prediction and use in Numerai tournament. Based on: https://www.kaggle.com/a763337092/pytorch-resnet-starter-training
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
A deep residual learning network for predicting lung adenocarcinoma
Analysis of various deep learning based models for financial time series data using convolutions, recurrent neural networks (lstm), dilated convolutions and residual learning
This is a Torch implementation of ["Deep Residual Learning for Image Recognition",Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun](http://arxiv.org/abs/1512.03385) the winners of the 2015 ILSVRC …