| Streaming keyword spotting on mobile devices O Rybakov, N Kononenko, N Subrahmanya, M Visontai, S Laurenzo arXiv preprint arXiv:2005.06720, 2020 | 149 | 2020 |
| 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 | 146 | 2009 |
| 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 | 112 | 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 | 81 | 2016 |
| 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 | 79 | 2008 |
| Adaptive divided difference filtering for simultaneous state and parameter estimation N Subrahmanya, YC Shin Automatica 45 (7), 1686-1693, 2009 | 74 | 2009 |
| Training keyword spotting models on non-iid data with federated learning A Hard, K Partridge, C Nguyen, N Subrahmanya, A Shah, P Zhu, ... arXiv preprint arXiv:2005.10406, 2020 | 55 | 2020 |
| Automated sensor selection and fusion for monitoring and diagnostics of plunge grinding N Subrahmanya, YC Shin | 54 | 2008 |
| 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 | 49 | 2013 |
| Improving Keyword Spotting and Language Identification via Neural Architecture Search at Scale PV Hanna Mazzawi, Xavi Gonzalvo, Aleks Kracun, Prashant Sridhar, Niranjan ... Interspeech 2019, 2019 | 45 | 2019 |
| 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 | 41 | 2010 |
| Geophysical inversion with convolutional neural networks H Denli, NA Subrahmanya US Patent 10,996,372, 2021 | 40 | 2021 |
| Constructive training of recurrent neural networks using hybrid optimization N Subrahmanya, YC Shin Neurocomputing 73 (13-15), 2624-2631, 2010 | 33 | 2010 |
| 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 | 32 | 2016 |
| 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 | 32 | 2013 |
| 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 | 25 | 2018 |
| Multi-scale Graphical Models for Spatio-Temporal Processes F Janoos, H Denli, N Subrahmanya Advances in Neural Information Processing Systems 27, 316-324, 2014 | 23 | 2014 |
| A variational Bayesian framework for group feature selection N Subrahmanya, YC Shin International Journal of Machine Learning and Cybernetics 4, 609-619, 2013 | 23 | 2013 |
| Automated seismic interpretation using fully convolutional neural networks DA Hernandez, NA Subrahmanya, DB Fitz-Gerald US Patent 11,119,235, 2021 | 21 | 2021 |
| Learning to detect keyword parts and whole by smoothed max pooling HJ Park, P Violette, N Subrahmanya ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 21 | 2020 |
Yung C. ShinDonald A. and Nancy G. Roach Distinguished Professor, Mechanical Engineering, Purdue Universityبريد إلكتروني تم التحقق منه على purdue.edu