most citedDetecting Anomalies within Time Series using Local Neural Transformations

8 citations · 9 across the 2 of their papers we have counts for

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cs.LG2022★ 1 cited

Robust Recurrent Neural Network to Identify Ship Motion in Open Water with Performance Guarantees -- Technical Report

Daniel Frank, Decky Aspandi Latif, Michael Muehlebach +2

Recurrent neural networks are capable of learning the dynamics of an unknown nonlinear system purely from input-output measurements. However, the resulting models do not provide an…

cs.LG2022★ 8 cited

Detecting Anomalies within Time Series using Local Neural Transformations

Tim Schneider, Chen Qiu, Marius Kloft +4

We develop a new method to detect anomalies within time series, which is essential in many application domains, reaching from self-driving cars, finance, and marketing to medical d…