4 papers
ARTA: Adversarial-Robust Multivariate Time--Series Anomaly Detection via Sparsity-Constrained Perturbations
Hadi Hojjati, Narges Armanfard
Time-series anomaly detection (TSAD) is a critical component in monitoring complex systems, yet modern deep learning-based detectors are often highly sensitive to localized input c…
EngineAD: A Real-World Vehicle Engine Anomaly Detection Dataset
Hadi Hojjati, Christopher Roth, Rory Woods +2
The progress of Anomaly Detection (AD) in safety-critical domains, such as transportation, is severely constrained by the lack of large-scale, real-world benchmarks. To address thi…
Collision-Aware Vision-Language Learning for End-to-End Driving with Multimodal Infraction Datasets
Alex Koran, Dimitrios Sinodinos, Hadi Hojjati +3
High infraction rates remain the primary bottleneck for end-to-end (E2E) autonomous driving, as evidenced by the low driving scores on the CARLA Leaderboard. Despite collision-rela…
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…