dengqi105's Stars
Event-AHU/Mamba_State_Space_Model_Paper_List
[Mamba-Survey-2024] Paper list for State-Space-Model/Mamba and it's Applications
ChenHongruixuan/ChangeDetectionRepository
This repository contains some python code of some traditional change detection methods or provides their original websites, such as SFA, MAD, and some deep learning-based change detection methods, such as SiamCRNN, DSFA, and some FCN-based methods.
liguge/Fault-diagnosis-for-small-samples-based-on-attention-mechanism
基于注意力机制的少量样本故障诊断 pytorch
xmindflow/Awesome_Mamba
Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis
thuml/SimMTM
About Code release for "SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling" (NeurIPS 2023 Spotlight), https://arxiv.org/abs/2302.00861
QinYi-team/Code
mingzhangPHD/Few-shot-Learning-for-Fault-Diagnosis
This repository is for the Few-shot Learning for the fault diagnosis of large industrial equipment.
liuxz1011/TodyNet
TodyNet: Temporal Dynamic Graph Neural Network for Multivariate Time Series Classification
LiangjunFeng/Industrial_ZSL
Source Code of Industrial_ZSL in TII
tinglixie/msf-rescnn-fd
code for TII paper "Intelligent Mechanical Fault Diagnosis Using Multi-Sensor Fusion and Convolution Neural Network"
GuokaiLiu/Awesome-Graph-Neural-Network-for-PHM
Early access articles, Journals, and Conferences
zhouyh310/SleepHGNN
This paper was submitted to ICASSP 2023: Exploiting Interactivity and Heterogeneity for Sleep Stage Classification via Heterogeneous Graph Neural Network
Everbright52/NEUFaultDiagnosis403
Innovative bearing fault diagnosis using SST algorithm for time-frequency images. Accurately transform signals into efficient time-frequency representations. Leverage deep learning for precise diagnosis. Open-source for collaboration, advancing bearing fault diagnosis.
liuzy0708/CFD-Datasets
Compound Fault Diagnosis Dataset of Rotating Machinery
ziyujia/PMIME-and-TE
Partial conditional mutual information from mixed embedding for coupling estimation in multivariate time series. We also use transfer entropy to realize this method.
fyancy/RaVEL
Fast Random Wavelet Kernel Convolution for Weak-Fault Diagnosis
OzerCanDevecioglu/Exploring-Sound-vs-Vibration-for-Robust-Fault-Detection-on-Rotating-Machinery
Rancho2050/PHM_LSF
ChenQian0618/Homepage
Homepage of ChenQian (chenqian2020.sjtu.edu.cn)
liguge/ESDNet
Learning A Spiking Neural Network for Efficient Image Deraining (IJCAI 2024)
liu331904724/DPHGNN
DPHGNN: A Dual Perspective Hypergraph Neural Networks [KDD'24 Paper]
BianZengXu/Fault-diagnosis-of-rolling-bearing-based-on-whvg-and-GCN_GIN
采用一种包含加权水平可见图(WHVG)的图卷积网络(GCN),对采样的轴承震动时间序列数据分析,进行滚动轴承故障诊断。其中,对HVG中两节点的边,以节点距离的倒数作为权重进行加权,以削弱噪声节点对其他距离较远节点的影响。
GuokaiLiu/PHMGNNBenchmark
this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.