MTV: Visual Analytics for Detecting, Investigating, and Annotating
Anomalies in Multivariate Time Series

MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series

10 December 2021

Sarah Alnegheimish

Alexandra Zytek

K. Veeramachaneni

Papers citing "MTV: Visual Analytics for Detecting, Investigating, and Annotating Anomalies in Multivariate Time Series"

9 / 9 papers shown

Title
Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing Sewoong Lee JinKyou Choi Min Su Kim AI4TS 14 0 0 20 Sep 2023
ActorLens: Visual Analytics for High-level Actor Identification in MOBA Games Zhihua Jin Gaoping Huang Zixin Chen Shiyi Liu Yang Chao Zhenchuan Yang Quan Li Huamin Qu 16 2 0 19 Jul 2023
From Explanation to Action: An End-to-End Human-in-the-loop Framework for Anomaly Reasoning and Management Xueying Ding Nikita Seleznev Senthil Kumar C. B. Bruss L. Akoglu 28 3 0 06 Apr 2023
DeepVATS: Deep Visual Analytics for Time Series V. Rodríguez-Fernández David Montalvo F. Piccialli Grzegorz J. Nalepa David Camacho AI4TS 19 7 0 08 Feb 2023
Towards Meaningful Anomaly Detection: The Effect of Counterfactual Explanations on the Investigation of Anomalies in Multivariate Time Series Max Schemmer Joshua Holstein Niklas Bauer Niklas Kühl G. Satzger 28 2 0 07 Feb 2023
Trust Calibration as a Function of the Evolution of Uncertainty in Knowledge Generation: A Survey J. Boley Maoyuan Sun 22 0 0 09 Sep 2022
RASIPAM: Interactive Pattern Mining of Multivariate Event Sequences in Racket Sports Jiang Wu Dongyu Liu Ziyang Guo Yingnian Wu 30 14 0 01 Aug 2022
Sintel: A Machine Learning Framework to Extract Insights from Signals Sarah Alnegheimish Dongyu Liu Carles Sala Cladellas Laure Berti-Equille K. Veeramachaneni AI4TS 16 15 0 19 Apr 2022
The Need for Interpretable Features: Motivation and Taxonomy Alexandra Zytek Ignacio Arnaldo Dongyu Liu Laure Berti-Equille K. Veeramachaneni FAtt XAI 6 13 0 23 Feb 2022