activity
20172022
most citedTracking System Behaviour from Resource Usage Data

8 citations · 15 across the 7 of their papers we have counts for

collaborators

12 papers

cs.LG2022

An Ensemble-Based Deep Framework for Estimating Thermo-Chemical State Variables from Flamelet Generated Manifolds

Amol Salunkhe, Georgios Georgalis, Abani Patra +1

Complete computation of turbulent combustion flow involves two separate steps: mapping reaction kinetics to low-dimensional manifolds and looking-up this approximate manifold durin…

cs.LG20211 cited

Anomaly Detection for High-Dimensional Data Using Large Deviations Principle

Sreelekha Guggilam, Varun Chandola, Abani Patra

Most current anomaly detection methods suffer from the curse of dimensionality when dealing with high-dimensional data. We propose an anomaly detection algorithm that can scale to…

stat.AP2020

ALPS: A Unified Framework for Modeling Time Series of Land Ice Changes

Prashant Shekhar, Beata Csatho, Tony Schenk +2

Modeling time series is a research focus in cryospheric sciences because of the complexity and multiscale nature of events of interest. Highly non-uniform sampling of measurements…

physics.geo-ph20201 cited

First application of the failure forecast method to the GPS horizontal displacement data collected in the Campi Flegrei caldera (Italy) in 2011-2020

Andrea Bevilacqua, Abani Patra, E. Bruce Pitman +8

Using the failure forecast method we describe a first assessment of failure time on present-day unrest signals at Campi Flegrei caldera (Italy) based on the horizontal deformation…

cs.LG20201 cited

Hierarchical regularization networks for sparsification based learning on noisy datasets

Prashant Shekhar, Abani Patra

We propose a hierarchical learning strategy aimed at generating sparse representations and associated models for large noisy datasets. The hierarchy follows from approximation spac…

stat.ML20194 cited

Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised)

Sreelekha Guggilam, Syed M. A. Zaidi, Varun Chandola +1

Most current clustering based anomaly detection methods use scoring schema and thresholds to classify anomalies. These methods are often tailored to target specific data sets with…