209 citations · 374 across the 12 of their papers we have counts for
4 papers · 1 filter
A Comprehensive Survey of Deep Transfer Learning for Anomaly Detection in Industrial Time Series: Methods, Applications, and Directions
Peng Yan, Ahmed Abdulkadir, Paul-Philipp Luley +4
Automating the monitoring of industrial processes has the potential to enhance efficiency and optimize quality by promptly detecting abnormal events and thus facilitating timely in…
Automated Machine Learning in Practice: State of the Art and Recent Results
Lukas Tuggener, Mohammadreza Amirian, Katharina Rombach +4
A main driver behind the digitization of industry and society is the belief that data-driven model building and decision making can contribute to higher degrees of automation and m…
Deep Learning in the Wild
Thilo Stadelmann, Mohammadreza Amirian, Ismail Arabaci +8
Deep learning with neural networks is applied by an increasing number of people outside of classic research environments, due to the vast success of the methodology on a wide range…
Learning Neural Models for End-to-End Clustering
Benjamin Bruno Meier, Ismail Elezi, Mohammadreza Amirian +2
We propose a novel end-to-end neural network architecture that, once trained, directly outputs a probabilistic clustering of a batch of input examples in one pass. It estimates a d…