21 citations · 26 across the 5 of their papers we have counts for
5 papers · 1 filter
MSAD: A Deep Dive into Model Selection for Time series Anomaly Detection
Emmanouil Sylligardos, John Paparrizos, Themis Palpanas +2
Anomaly detection is a fundamental task for time series analytics with important implications for the downstream performance of many applications. Despite increasing academic inter…
MLLM4TS: Leveraging Vision and Multimodal Language Models for General Time-Series Analysis
Qinghua Liu, Sam Heshmati, Zheda Mai +3
Effective analysis of time series data presents significant challenges due to the complex temporal dependencies and cross-channel interactions in multivariate data. Inspired by the…
VUS: Effective and Efficient Accuracy Measures for Time-Series Anomaly Detection
Paul Boniol, Ashwin K. Krishna, Marine Bruel +7
Anomaly detection (AD) is a fundamental task for time-series analytics with important implications for the downstream performance of many applications. In contrast to other domains…
Dive into Time-Series Anomaly Detection: A Decade Review
Paul Boniol, Qinghua Liu, Mingyi Huang +2
Recent advances in data collection technology, accompanied by the ever-rising volume and velocity of streaming data, underscore the vital need for time series analytics. In this re…
Band-limited Training and Inference for Convolutional Neural Networks
Adam Dziedzic, John Paparrizos, Sanjay Krishnan +2
The convolutional layers are core building blocks of neural network architectures. In general, a convolutional filter applies to the entire frequency spectrum of the input data. We…