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cs.LG2026
A Multi-directional Meta-Learning Framework for Class-Generalizable Anomaly Detection
Padmaksha Roy, Lamine Mili, Almuatazbellah Boker
In this paper, we address the problem of class-generalizable anomaly detection, where the objective is to develop a unified model by focusing our learning on the available normal d…
cs.LG2025
Beyond Marginals: Learning Joint Spatio-Temporal Patterns for Multivariate Anomaly Detection
Padmaksha Roy, Almuatazbellah Boker, Lamine Mili
In this paper, we aim to improve multivariate anomaly detection (AD) by modeling the \textit{time-varying non-linear spatio-temporal correlations} found in multivariate time series…
cs.LG2024
A Latent Space Correlation-Aware Autoencoder for Anomaly Detection in Skewed Data
Padmaksha Roy
Unsupervised learning-based anomaly detection in latent space has gained importance since discriminating anomalies from normal data becomes difficult in high-dimensional space. Bot…