Niranjan Subrahmanya
TitleCited byYear
Sparse multiple kernel learning for signal processing applications
N Subrahmanya, YC Shin
IEEE Transactions on Pattern Analysis and Machine Intelligence 32 (5), 788-798, 2009
Adaptive divided difference filtering for simultaneous state and parameter estimation
N Subrahmanya, YC Shin
Automatica 45 (7), 1686-1693, 2009
Generalized practical models of cylindrical plunge grinding processes
TJ Choi, N Subrahmanya, H Li, YC Shin
International journal of machine tools and manufacture 48 (1), 61-72, 2008
Granger causality for time-series anomaly detection
H Qiu, Y Liu, NA Subrahmanya, W Li
2012 IEEE 12th international conference on data mining, 1074-1079, 2012
Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction
P Sadowski, D Fooshee, N Subrahmanya, P Baldi
Journal of Chemical Information and Modeling, 2016
Cold Start Approach For Data Driven Fault Detection
M Grbovic, W Li, N Subrahmanya, A Usadi, S Vucetic
Industrial Informatics, IEEE Transactions on, 1-1, 2013
Constructive training of recurrent neural networks using hybrid optimization
N Subrahmanya, YC Shin
Neurocomputing 73 (13-15), 2624-2631, 2010
Automated sensor selection and fusion for monitoring and diagnostics of plunge grinding
N Subrahmanya, YC Shin
Journal of manufacturing science and engineering 130 (3), 031014, 2008
A Bayesian machine learning method for sensor selection and fusion with application to on-board fault diagnostics
N Subrahmanya, YC Shin, PH Meckl
Mechanical Systems and Signal Processing 24 (1), 182-192, 2010
A data-based framework for fault detection and diagnostics of non-linear systems with partial state measurement
N Subrahmanya, YC Shin
Engineering Applications of Artificial Intelligence 26 (1), 446-455, 2013
Method for automatic control and positioning of autonomous downhole tools
K Kumaran, NA Subrahmanya, PB Entchev, RC Tolman, RMA Boza
US Patent 9,328,578, 2016
A variational bayesian framework for group feature selection
N Subrahmanya, YC Shin
International Journal of Machine Learning and Cybernetics 4 (6), 609-619, 2013
Multi-scale Graphical Models for Spatio-Temporal Processes
F Janoos, H Denli, N Subrahmanya
Advances in Neural Information Processing Systems 27, 316-324, 2014
Inner and outer recursive neural networks for chemoinformatics applications
G Urban, N Subrahmanya, P Baldi
Journal of chemical information and modeling 58 (2), 207-211, 2018
Model-Based Optimization of the OD Plunge Grinding Process via Generalized Intelligent Grinding Advisory System (GIGAS)”,
N Subrahmanya, T Choi, YC Shin
Transactions of the North American Manufacturing Research Institution 35 …, 2007
Determining Interwell Communication
W Li, NA Subrahmanya, L Song, AK Usadi, K Kumaran, P Xu, ...
US Patent App. 13/646,363, 2013
Advanced Machine Learning Methods for Production Data Pattern Recognition
N Subrahmanya, P Xu, A El-Bakry, C Reynolds
SPE Intelligent Energy Conference & Exhibition, 2014
Online subspace and sparse filtering for target tracking in reverberant environment
W Li, N Subrahmanya, F Xu
2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM …, 2012
Identification of recurrent patterns in the activation of brain networks
F Janoos, W Li, N Subrahmanya, I Morocz, W Wells
Advances in Neural Information Processing Systems, 674-682, 2012
Autonomous Perforating System for Multizone Completions
PB Entchev, R Angeles, K Kumaran, N Subrahmanya, RC Tolman
SPE Annual Technical Conference and Exhibition, 2011
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Articles 1–20