Name
Abstract | ||
|---|---|---|
There are numerous methods for detecting anomalies in time series, but that is only the first step to understanding them. We strive to exceed this by explaining those anomalies. Thus we develop a novel attribution scheme for multivariate time series relying on counterfactual reasoning. We aim to answer the counterfactual question of would the anomalous event have occurred if the subset of the invo... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICMLA52953.2021.00033 | 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA) |
Keywords | DocType | ISBN |
Heating systems,Correlation,Time series analysis,Distributed databases,Machine learning,Cognition,Hurricanes | Conference | 978-1-6654-4337-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Violeta Teodora Trifunov | 1 | 0 | 0.34 |
| Maha Shadaydeh | 2 | 17 | 4.33 |
| Björn Barz | 3 | 0 | 0.34 |
| Joachim Denzler | 4 | 985 | 103.50 |