Yi Jiang (SakuraAyase)

SakuraAyase

Geek Repo

Company:South China University of Technology

Location:Guangzhou, China

Home Page:sakuraayase.github.io

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Yi Jiang's starred repositories

wxpy

微信机器人 / 可能是最优雅的微信个人号 API ✨✨

Language:PythonLicense:MITStargazers:13876Issues:551Issues:429

deap

Distributed Evolutionary Algorithms in Python

Language:PythonLicense:LGPL-3.0Stargazers:5650Issues:191Issues:512

scikit-opt

Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)

Language:PythonLicense:MITStargazers:5035Issues:45Issues:176

dimensionality_reduction_alo_codes

特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

Language:PythonLicense:Apache-2.0Stargazers:2248Issues:43Issues:5

PlatEMO

Evolutionary multi-objective optimization platform

Evolutionary-Algorithm

Evolutionary Algorithm using Python, 莫烦Python 中文AI教学

Language:PythonLicense:MITStargazers:1181Issues:65Issues:16

opennn

OpenNN - Open Neural Networks Library

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pytorch2keras

PyTorch to Keras model convertor

Language:PythonLicense:MITStargazers:853Issues:14Issues:127

TSP_collection

TSP算法全复现:遗传(GA)、粒子群(PSO)、模拟退火(SA)、禁忌搜索(ST)、蚁群算法(ACO)、自自组织神经网络(SOM)

UAVS

Intelligent UAV path planning simulation system is a software with fine operation control, strong platform integration, omnidirectional model building and application automation. It takes the UAV war between A and B in Zone C as the background. The core function of the system is to plan the UAV route through the simulation platform and verify the output. The data can be imported into the real UAV to make it accurately arrive at any position in the battlefield according to the specified route and support the joint action of multi-person and multi-device formation.

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Hypernets

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Language:PythonLicense:Apache-2.0Stargazers:260Issues:19Issues:23

MER

Fork of the GEM project (https://github.com/facebookresearch/GradientEpisodicMemory) including Meta-Experience Replay (MER) methods from the ICLR 2019 paper (https://openreview.net/pdf?id=B1gTShAct7)

Language:PythonLicense:Apache-2.0Stargazers:143Issues:6Issues:4

MTO-Platform

Multitask Optimization Platform (MToP): A MATLAB Optimization Platform for Evolutionary Multitasking

ENAS-Keras

Keras implementation of Efficient Neural Architecture Search

darts-tensorflow

Tensorflow code for Differentiable architecture search

pymap_elites

map elites python reference implementation

Language:PythonLicense:NOASSERTIONStargazers:72Issues:8Issues:5

cec2017-py

Python module for CEC 2017 single objective optimization test function suite.

Language:PythonLicense:MITStargazers:68Issues:1Issues:3

pc-protector-moe

护萌宝 战舰少女R 游戏辅助 电脑版

Language:PythonLicense:GPL-3.0Stargazers:54Issues:7Issues:0

Evolutionary-Optimization-Algorithms

DE, CMA-ES, MA-ES, LM-MAES Python Implementation

Language:PythonLicense:MITStargazers:27Issues:1Issues:0
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cec2019comp100digit

Wrapper in Python for the CEC'2019 100 digit competition at http://cec2019.org/programs/competitions.html#cec-06

Language:C++License:MITStargazers:16Issues:2Issues:3

OS-exp

experiments for Course 'Advanced Operation System'.

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cec-benchmark-2013-python

for testing metaheuristic algorithm which is specific for continuous search spaces like Particle Swarm optimizations, Differential evolutions, etc, one can be sure about the performances of algorithm bt testing them in this benchmark. benchmark has been defined by IEEE World Congress on Computational Intelligence in C++. then developers implemented them in MATLAB and R. Now I have implemented them in Python as these language getting hit between data scientists a lot. I hope you find it useful.

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SPS-DE

Successful-Parent-Selecting Differential Evolution

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Moving-Peaks-Benchmark

Evolutionary Algorithms in Dynamic Environments

Language:C++Stargazers:8Issues:2Issues:0

Advanced-Metaheuristics-LSGO

This repo contains my Computer Engineering Degree's Final Project, studied at the University of Granada, Spain. The main focus is to apply state-of-the-art metaheuristic algorithms into a Big Optimization problem with thousands of variables. Our task is to find out how accurate are theoretical benchmark results compared to real EEG (Electroencephalography) data

Language:CLicense:GPL-3.0Stargazers:6Issues:1Issues:1

ENAS-keras-ModelBuilder

ENAS-keras ModelBuilder

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ma2bea

Many-task Multi-Armed Bandit Evolutionary Algorithm

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