92 citations · 183 across the 23 of their papers we have counts for
5 papers · 1 filter
Unveiling the Flaws: A Critical Analysis of Initialization Effect on Time Series Anomaly Detection
Alex Koran, Hadi Hojjati, Narges Armanfard
Deep learning for time-series anomaly detection (TSAD) has gained significant attention over the past decade. Despite the reported improvements in several papers, the practical app…
Forward-Backward Knowledge Distillation for Continual Clustering
Mohammadreza Sadeghi, Zihan Wang, Narges Armanfard
Unsupervised Continual Learning (UCL) is a burgeoning field in machine learning, focusing on enabling neural networks to sequentially learn tasks without explicit label information…
Deep Clustering with Self-Supervision using Pairwise Similarities
Mohammadreza Sadeghi, Narges Armanfard
Deep clustering incorporates embedding into clustering to find a lower-dimensional space appropriate for clustering. In this paper, we propose a novel deep clustering framework wit…
Graph-Jigsaw Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection
Ali Karami, Thi Kieu Khanh Ho, Narges Armanfard
Skeleton-based video anomaly detection (SVAD) is a crucial task in computer vision. Accurately identifying abnormal patterns or events enables operators to promptly detect suspicio…
Cross-Task Affinity Learning for Multitask Dense Scene Predictions
Dimitrios Sinodinos, Narges Armanfard
Multitask learning (MTL) has become prominent for its ability to predict multiple tasks jointly, achieving better per-task performance with fewer parameters than single-task learni…