Guokai Liu's repositories
Awesome-Graph-Neural-Network-for-PHM
Early access articles, Journals, and Conferences
convnet-noisy
convolutional code for feed-forward noise model
fault-diagnosis-NAS-PERIRB
NAS-FDD
PHMGNNBenchmark
this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.
awesome-AutoML
Curating a list of AutoML-related research, tools, projects and other resources
awesome-imbalanced-learning
A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习:论文、代码、框架与库
BAGAN
Keras implementation of Balancing GAN (BAGAN) applied to the MNIST example.
cbm_codes_open
This repository contains data and code that implement common machine learning algorithms for machinery condition monitoring task.
Defect-GLM
Defect-GLM:A Large Visual-Language Model for Industrial Defect Monitoring|首个用于工业缺陷监测的开源大规模视觉语言模型
FedML
A Research-oriented Federated Learning Library. Supporting distributed computing, mobile/IoT on-device training, and standalone simulation. Best Paper Award at NeurIPS 2020 Federated Learning workshop. Join our Slack Community:(https://join.slack.com/t/fedml/shared_invite/zt-havwx1ee-a1xfOUrATNfc9DFqU~r34w)
HUST-PhD-Thesis-Latex
华中科技大学博士毕业论文Latex模板
MetaFD
The source codes of Meta-learning for few-shot cross-domain fault diagnosis.
pydata-sphinx-theme
A clean, three-column Sphinx theme with Bootstrap for the PyData community
PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
RTD
Read the Docs Online Notes
smote_variants
A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
styles
Official repository for Citation Style Language (CSL) citation styles.
wt-fdd
Wind Turbine Fault Detection.
WT-planetary-gearbox-dataset
WT-planetary-gearbox-datasets