ChocalateWZLH

Fault_frequency_learning

MATLAB codes for "Bearing fault diagnosis with frequency sparsity learning"

Graph-Dynamic-Autoencoder

Code for thesis "Graph Dynamic Autoencoder for Fault Detection"

ADD-GCN

ADD-GCN: Attention-Driven Dynamic Graph Convolutional Network for Multi-Label Image Recognition (ECCV 2020)

ASL

Official Pytorch Implementation of: "Asymmetric Loss For Multi-Label Classification"(ICCV, 2021) paper

data_driven_features_ims

Multiclass bearing fault classification using features learned by a deep neural network.

Deep-Residual-Shrinkage-Networks

The deep residual shrinkage network is a variant of deep residual networks.

deep-sparse

We introduce a way to extend sparse dictionary learning to deep architectures.

DICTOL

DICTOL - A Dictionary Learning Toolbox in Matlab and Python

DICTOL_python

A Python implementation of well-known dictionary learning methods.

fault-dataset-collection

This repository collect some datasets for bearings and gearboxes

Few-Shot

A PyTorch implementation of a few shot, and meta-learning algorithms for image classification.

GDCAN

[TPAMI 2021] Code release for "Generalized Domain Conditioned Adaptation Network" https://arxiv.org/abs/2103.12339

GDL

Code for Online Graph Dictionary Learning

gmm-torch

Gaussian mixture models in PyTorch.

GNNPapers

Must-read papers on graph neural networks (GNN)

HIconstruct_optimize

Contains code to compare several health index construction methods using run-to-failure bearing dataset

MCD_DA

meta-transfer-learning

TensorFlow and PyTorch implementation of "Meta-Transfer Learning for Few-Shot Learning" (CVPR2019)

PyTorch-Transformer-for-RUL-Prediction

Transformer implementation with PyTorch for remaining useful life prediction on turbofan engine with NASA CMAPSS data set. Inspired by Mo, Y., Wu, Q., Li, X., & Huang, B. (2021). Remaining useful life estimation via transformer encoder enhanced by a gated convolutional unit. Journal of Intelligent Manufacturing, 1-10.

PyTorch-VAE

A Collection of Variational Autoencoders (VAE) in PyTorch.

RUL-prediction-using-attention-based-deep-learning-approach

SDNet

An official codebase of paper "Revisiting Sparse Convolutional Model for Visual Recognition"

SparseScatNet

Code implementation of paper: Deep Network Classification by Scattering and Homotopy Dictionary Learning

Supplementary-Dataset

This is the original dataset that we use in our research work, but it may difficult to find in the original link.

UDTL_multi_domain

Unsupervised Deep Transfer Learning for Intelligent Fault Diagnosis: An Open Source and Comparative Study (multi_domain))

VeRI_SSML_FD

Unsupervised Vehicle Re-Identification via Self-Supervised Metric Learning using Feature Dictionary

WaveletFCNN

Source code and dataset for the paper ""

weibull-knowledge-informed-ml

Using knowledge-informed machine learning on the PRONOSTIA (FEMTO) and IMS bearing data sets. Predict remaining-useful-life (RUL).

wwww.github.io

ZS_SDL

Official Pytorch Implementation of: "Semantic Diversity Learning for Zero-Shot Multi-label Classification"(ICCV, 2021) paper