159 citations · 331 across the 6 of their papers we have counts for
6 papers
CEDL: Centre-Enhanced Discriminative Learning for Anomaly Detection
Zahra Zamanzadeh Darban, Qizhou Wang, Charu C. Aggarwal +3
Supervised anomaly detection methods perform well in identifying known anomalies that are well represented in the training set. However, they often struggle to generalise beyond th…
GenIAS: Generator for Instantiating Anomalies in time Series
Zahra Zamanzadeh Darban, Qizhou Wang, Geoffrey I. Webb +3
Synthetic anomaly injection is a recent and promising approach for time series anomaly detection (TSAD), but existing methods rely on ad hoc, hand-crafted strategies applied to raw…
MTP: A Dataset for Multi-Modal Turning Points in Casual Conversations
Gia-Bao Dinh Ho, Chang Wei Tan, Zahra Zamanzadeh Darban +3
Detecting critical moments, such as emotional outbursts or changes in decisions during conversations, is crucial for understanding shifts in human behavior and their consequences.…
DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series
Zahra Zamanzadeh Darban, Yiyuan Yang, Geoffrey I. Webb +4
In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solutio…
CARLA: Self-supervised Contrastive Representation Learning for Time Series Anomaly Detection
Zahra Zamanzadeh Darban, Geoffrey I. Webb, Shirui Pan +2
One main challenge in time series anomaly detection (TSAD) is the lack of labelled data in many real-life scenarios. Most of the existing anomaly detection methods focus on learnin…
GHRS: Graph-based Hybrid Recommendation System with Application to Movie Recommendation
Zahra Zamanzadeh Darban, Mohammad Hadi Valipour
Research about recommender systems emerges over the last decade and comprises valuable services to increase different companies' revenue. Several approaches exist in handling paper…