30 citations · 30 across the 1 of their papers we have counts for
3 papers
Semi-Supervised Learning of Bearing Anomaly Detection via Deep Variational Autoencoders
Shen Zhang, Fei Ye, Bingnan Wang +1
Most of the data-driven approaches applied to bearing fault diagnosis up to date are established in the supervised learning paradigm, which usually requires a large set of labeled…
Machine Learning and Deep Learning Algorithms for Bearing Fault Diagnostics -- A Comprehensive Review
Shen Zhang, Shibo Zhang, Bingnan Wang +1
In this survey paper, we systematically summarize existing literature on bearing fault diagnostics with machine learning (ML) and data mining techniques. While conventional ML meth…
Deep Neural Network Inverse Design of Integrated Nanophotonic Devices
Mohammad H. Tahersima, Keisuke Kojima, Toshiaki Koike-Akino +4
Predicting physical response of an artificially structured material is of particular interest for scientific and engineering applications. Here we use deep learning to predict opti…