Neural Contextual Anomaly Detection for Time Series
Authors: Chris U. Carmona, François-Xavier Aubet, Valentin Flunkert, Jan Gasthaus
IJCAI 2022 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate empirically on standard benchmark datasets that our approach obtains a state-of-the-art performance in the supervised, semi-supervised, and unsupervised settings. |
| Researcher Affiliation | Industry | Chris U. Carmona , Franc ois-Xavier Aubet , Valentin Flunkert , Jan Gasthaus Amazon Research {chrcarm, aubetf, flunkert, gasthaus}@amazon.com |
| Pseudocode | No | No pseudocode or clearly labeled algorithm blocks are present in the paper. The steps for the method are described in prose. |
| Open Source Code | Yes | open-source code of NCAD is available 2); 2https://github.com/awslabs/gluon-ts/tree/master/src/gluonts/ nursery/ncad |
| Open Datasets | Yes | We benchmark our method to others on five datasets... For the multivariate setting, we use: Soil Moisture Active Passive satellite (SMAP) and Mars Science Laboratory rover (MSL), two datasets published by NASA [Hundman et al., 2018]; and Server Machine Dataset (SMD)... For the univariate setting, we use: YAHOO, a dataset by [Yahoo! Labs, 2015]... And KPI, univariate dataset released in the AIOPS data competition by [Tsinghua Netman Lab, 2018]. |
| Dataset Splits | Yes | For both, following [Ren et al., 2019], we use the last 50% of the time points of each of the time series as test set and split the rest in 30% training and 20% validation set. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory specifications) used for running the experiments are provided in the paper. |
| Software Dependencies | No | No specific software dependencies with version numbers (e.g., library names with versions) are listed in the paper. |
| Experiment Setup | Yes | Hyperparameters were chosen using the validation set for YAHOO and KPI, and a standard setting is inferred for the other datasets (see extended article for details1). |