IIB Master's Project: Deep Learning for Koopman Optimal Predictive Control

Deep invertible Koopman operator with control model (DIKU) and adversarial sampling of DIKU (ASKU) for online time-informed set approximation

《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 代码。简体版和繁体版同步更新，English version ongoing

neural networks to learn Koopman eigenfunctions

A data-driven framework for control of nonlinear flows with Koopman Model Predictive Control

Koopman Reduced-Order Nonlinear Identification and Control

Software to train neural networks via Koopman operator theory (see Dogra and Redman "Optimizing Neural Networks via Koopman Operator Theory" NeurIPS 2020 for details).

All the code needed to learn models from data using Koopman operator approach.

Koopman Mode Decomposition

A package for computing data-driven approximations to the Koopman operator.

A library for Koopman Neural Operator with Pytorch.

AutoKoopman - automated Koopman operator methods for data-driven dynamical systems analysis and control.

Data-driven Koopman control theory applied to reinforcement learning!

Code release for "Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors" (NeurIPS 2023), https://arxiv.org/abs/2305.18803

All scripts and code related to the thesis, based on Koopman operators

Supplemental code for "Auto-Generation of Mission-Oriented Robot Controllers Using Bayesian-Based Koopman Operator"

MSIFT: A Novel End-to-End Mechanical Fault Diagnosis Framework under Limited & Imbalanced Data Using Multi-Source Information Fusion

A repository containing the code for an article on approaching an imbalanced classification problem

2008-2012 Roadster Development and Diagnostic Software files

Source code for Twitter's Recommendation Algorithm

Code for CRATE (Coding RAte reduction TransformEr).