1 citations · 2 across the 5 of their papers we have counts for
5 papers
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…
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…
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning
Padmaksha Roy, Jaganmohan Chandrasekaran, Erin Lanus +2
Machine learning (ML) is increasingly being deployed in critical systems. The data dependence of ML makes securing data used to train and test ML-enabled systems of utmost importan…
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…
Deep diffusion-based forecasting of COVID-19 by incorporating network-level mobility information
Padmaksha Roy, Shailik Sarkar, Subhodip Biswas +4
Modeling the spatiotemporal nature of the spread of infectious diseases can provide useful intuition in understanding the time-varying aspect of the disease spread and the underlyi…