chendingliang

Bayesian-Neural-Networks

Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more

HIconstruct_optimize

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

HNUIDG-Fault-Diagnosis-

The intelligent fault diagnosis of HNU IDG

Hyperparameter-Tuning-In-LSTM-Network

Hyperparameter Tuning in LSTM using Genetic Algorithm, Bayesian Optimization, Random Search, Grid Search.

KPCA-MATLAB

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

MACNN

Multi-scale Attention Convolutional Neural Network for Time Series Classification

ML_Notes

机器学习算法的公式推导以及numpy实现

prml

Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

PyTorch-LSTM-for-RUL-Prediction

PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., & Gupta, C. (2017, June). Long short-term memory network for remaining useful life estimation.

Remaining-Useful-Life-Prediction-for-Turbofan-Engines

RUL prediction for Turbofan Engine (CMAPSS dataset) using CNN

chendingliang/PyTorch-LSTM-for-RUL-Prediction

PyTorch implementation of remaining useful life prediction with long-short term memories (LSTM), performing on NASA C-MAPSS data sets. Partially inspired by Zheng, S., Ristovski, K., Farahat, A., & Gupta, C. (2017, June). Long short-term memory network for remaining useful life estimation.

chendingliang/HIconstruct_optimize

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

chendingliang/HNUIDG-Fault-Diagnosis-

The intelligent fault diagnosis of HNU IDG

chendingliang/KPCA-MATLAB

MATLAB code for dimensionality reduction, feature extraction, fault detection, and fault diagnosis using Kernel Principal Component Analysis (KPCA).

chendingliang/ML_Notes

机器学习算法的公式推导以及numpy实现

chendingliang/prml

Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

chendingliang/weibull-knowledge-informed-ml

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

chendingliang/Wind_Turbine_SCADA_open_data

list of open data wind turbine data sets

chendingliang/Audio-Digital-Processing

数字信号处理大作业：Matlab实现语音分析：加噪声，频谱分析，滤波器等等（内附报告）【Matlab for speech analysis: add noise, spectrum analysis, filter, etc】

chendingliang/awesome-awesome-machine-learning

A curated list of awesome lists across all machine learning topics. | 机器学习/深度学习/人工智能一切主题 (学习范式/任务/应用/模型/道德/交叉学科/数据集/框架/教程) 的资源列表汇总。

chendingliang/bayesian-mixture-of-gaussians

Numpy code for Coordinate Ascent Variational Inference for the Bayesian mixture of Gaussians model (Sec 10.2 of Bishop's PRML).

chendingliang/BayesianOptimization

A Python implementation of global optimization with gaussian processes.

chendingliang/CADA

This is a github repository for Adversarial transfer learning with constrastive coding for time series regression problem.

chendingliang/competition-baseline

数据科学竞赛知识、代码、思路

chendingliang/deep-learning-time-series

List of papers, code and experiments using deep learning for time series forecasting

chendingliang/examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

chendingliang/GMM-EM-Python

Python implementation of EM algorithm for GMM. And visualization for 2D case.

chendingliang/gmm-torch

Gaussian mixture models in PyTorch.

chendingliang/Hands-On-Meta-Learning-With-Python

Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow

chendingliang/https-github.com-luwill-Machine_Learning_Code_Implementation

chendingliang/Mini-blp-lplq

The Matlab code of blind deconvolution based on criterion defined by envelope spectrum

chendingliang/MLAPP_CN_CODE

《Machine Learning: A Probabilistic Perspective》（Kevin P. Murphy）中文翻译和书中算法的Python实现。

chendingliang/PHMGNNBenchmark

this code library is mainly about applying graph neural networks to intelligent diagnostic and prognostic.

chendingliang/PyTorch-CNN-for-RUL-Prediction

PyTorch implementation of CNN for remaining useful life prediction. Inspired by Babu, G. S., Zhao, P., & Li, X. L. (2016, April). Deep convolutional neural network-based regression approach for estimation of remaining useful life. In International conference on database systems for advanced applications (pp. 214-228). Springer, Cham.

chendingliang/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.

chendingliang/PyTorchIntroduction

《深入浅出 PyTorch——从模型到源码》源代码和勘误（见Issues）

chendingliang/Remaining-Useful-Life-Estimation-Variational

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

chendingliang/siamese-triplet

Siamese and triplet networks with online pair/triplet mining in PyTorch

chendingliang/Transfer-Learning-Library

Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization