Bayesian structure learning with generative flow networks T Deleu, A Góis, C Emezue, M Rankawat, S Lacoste-Julien, S Bauer, ... Uncertainty in Artificial Intelligence, 518-528, 2022 | 100 | 2022 |
Determining drivable free-space for autonomous vehicles M Rankawat, J Yao, D Zhang, CC Chen US Patent 11,537,139, 2022 | 83 | 2022 |
ECG artifacts detection in noncardiovascular signals using Slope Sum Function and Teager Kaiser Energy SA Rankawat, M Rankawat, R Dubey 2015 International Conference on BioSignal Analysis, Processing and Systems …, 2015 | 13 | 2015 |
Heart rate estimation from non-cardiovascular signals using slope sum function and Teager energy SA Rankawat, M Rankawat, R Dubey 2015 International Conference on Industrial Instrumentation and Control …, 2015 | 5 | 2015 |
A priori guarantees of finite-time convergence for Deep Neural Networks A Rankawat, M Rankawat, HB Oza arXiv preprint arXiv:2009.07509, 2020 | | 2020 |
Detecting Fast Radio Bursts Using Convolutional Neural Networks A Rankawat, M Rankawat, GR Harp 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC), 2018 | | 2018 |
Narrow-band signal classification using Deep Convolutional Neural Networks M Rankawat, GR Harp 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC), 1-1, 2018 | | 2018 |
Deep Convolutional Neural Networks for the Generation of High Fidelity Images from Radio Interferometer Visibility Data GR Harp, M Rankawat 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC), 1-1, 2018 | | 2018 |
Voice Activity Detection using Temporal Characteristics of Autocorrelation Lag and Maximum Spectral Amplitude in Sub-bands S Achanta, N Chennupati, V Pannala, M Rankawat, K Prahallad Proceedings of the 11th International Conference on Natural Language …, 2014 | | 2014 |
Real time voice activity detection for conversational scene analysis M Rankawat Dhirubhai Ambani Institute of Information and Communication Technology, 2014 | | 2014 |