Name: Zhaofeng Liu
Type: User
Company: School of Automation Hangzhou Dianzi University
Bio: Master Student, Control Science and Engineering, School of Automation Hangzhou Dianzi University.
Location: Hangzhou, Zhejiang, China PR
Zhaofeng Liu 's Projects
Remaining useful life prediction for turbofan engine data (C-MAPSS)
Attention-based multihead model for optimized aircraft engine remaining useful life prediction
Remaining Useful Life (RUL) estimation of Lithium-ion batteries using deep LSTMs
Implementation of Bayesian Recurrent Neural Networks by Fortunato et. al
An implementation of the BERT model and its related downstream tasks based on the PyTorch framework
完整的航空发动机一维卷积神经网络训练模型
A neural network model for Chinese named entity recognition
Code for the paper "LSTM Networks for Data-Aware Remaining Time Prediction of Business Process Instances"
The code of DAST
Deep learning in PHM,Deep learning in fault diagnosis,Deep learning in remaining useful life prediction
This filder contains most important works that i have made with deoinsing Autoencoders.
A simple probabilistic programming language.
False Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
The GitHub repository for the paper "Informer" accepted by AAAI 2021.
Keras Temporal Convolutional Network.
Tool wear prediction by residual CNN
LAVIS - A One-stop Library for Language-Vision Intelligence
🎨 ML Visuals contains figures and templates which you can reuse and customize to improve your scientific writing.
Models and examples built with TensorFlow
Multi-Scale Temporal-Spatial Feature-based Hybrid Deep Neural Network (MSTSDN) for Predicting RUL of Aero-engine.
Remaining Useful Life (NASA CMAPS Dataset)
Bayesian Convolutional Neural Network with Variational Inference based on Bayes by Backprop in PyTorch.
Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine
Companion repository for the paper "Improving Semi-Supervised Learning for Remaining Useful Lifetime Estimation Through Self-Supervision".
Source code of the paper "A stacked DCNN to predict the RUL of a turbofan engine", third place ranked in the PHM21 data challenge.
Sequence modeling benchmarks and temporal convolutional networks