8 citations · 19 across the 9 of their papers we have counts for
18 papers
Geo-Adaptive Deep Spatio-Temporal predictive modeling for human mobility
Syed Mohammed Arshad Zaidi, Varun Chandola, EunHye Yoo
Deep learning approaches for spatio-temporal prediction problems such as crowd-flow prediction assumes data to be of fixed and regular shaped tensor and face challenges of handling…
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…
Physics Informed Machine Learning for Chemistry Tabulation
Amol Salunkhe, Dwyer Deighan, Paul Desjardin +1
Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Inste…
ChemTab: A Physics Guided Chemistry Modeling Framework
Amol Salunkhe, Dwyer Deighan, Paul DesJardin +1
Modeling of turbulent combustion system requires modeling the underlying chemistry and the turbulent flow. Solving both systems simultaneously is computationally prohibitive. Inste…
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…
From images in the wild to video-informed image classification
Marc Böhlen, Varun Chandola, Wawan Sujarwo +1
Image classifiers work effectively when applied on structured images, yet they often fail when applied on images with very high visual complexity. This paper describes experiments…