| Flexpoint: An adaptive numerical format for efficient training of deep neural networks U Köster, T Webb, X Wang, M Nassar, AK Bansal, W Constable, O Elibol, ... Advances in neural information processing systems 30, 2017 | 333 | 2017 |
| Impulsive noise mitigation in powerline communications using sparse Bayesian learning J Lin, M Nassar, BL Evans IEEE Journal on Selected Areas in Communications 31 (7), 1172-1183, 2013 | 296 | 2013 |
| Local utility power line communications in the 3–500 kHz band: Channel impairments, noise, and standards M Nassar, J Lin, Y Mortazavi, A Dabak, IH Kim, BL Evans IEEE signal processing magazine 29 (5), 116-127, 2012 | 257 | 2012 |
| Cyclostationary Noise Modeling in Narrowband Powerline Communication for Smart Grid Applications M Nassar, A Dabak, IH Kim, T Pande, BL Evans ICASSP, 0 | 159* | |
| Mitigating near-field interference in laptop embedded wireless transceivers M Nassar, K Gulati, MR DeYoung, BL Evans, KR Tinsley Journal of Signal Processing Systems 63, 1-12, 2011 | 106 | 2011 |
| Statistical modeling of asynchronous impulsive noise in powerline communication networks M Nassar, K Gulati, Y Mortazavi, BL Evans 2011 IEEE Global Telecommunications Conference-GLOBECOM 2011, 1-6, 2011 | 98 | 2011 |
| A factor graph approach to joint OFDM channel estimation and decoding in impulsive noise environments M Nassar, P Schniter, BL Evans IEEE Transactions on Signal Processing 62 (6), 1576-1589, 2013 | 84 | 2013 |
| System and method for a unified architecture multi-task deep learning machine for object recognition M El-Khamy, A Yedla, M Nassar, J Lee US Patent 10,032,067, 2018 | 72 | 2018 |
| Cyclic spectral analysis of power line noise in the 3–200 kHz band KF Nieman, J Lin, M Nassar, K Waheed, BL Evans 2013 IEEE 17th International Symposium on Power Line Communications and Its …, 2013 | 60 | 2013 |
| Connection management xAPP for O-RAN RIC: A graph neural network and reinforcement learning approach O Orhan, VN Swamy, T Tetzlaff, M Nassar, H Nikopour, S Talwar 2021 20th IEEE international conference on machine learning and applications …, 2021 | 52 | 2021 |
| System and method for a deep learning machine for object detection A Yedla, M Nassar, M El-Khamy, J Lee US Patent 10,380,741, 2019 | 47 | 2019 |
| Non-parametric impulsive noise mitigation in OFDM systems using sparse Bayesian learning J Lin, M Nassar, BL Evans 2011 IEEE Global Telecommunications Conference-GLOBECOM 2011, 1-5, 2011 | 33 | 2011 |
| Structured citation trend prediction using graph neural networks D Cummings, M Nassar ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 29 | 2020 |
| IAB topology design: A graph embedding and deep reinforcement learning approach M Simsek, O Orhan, M Nassar, O Elibol, H Nikopour IEEE Communications Letters 25 (2), 489-493, 2020 | 26 | 2020 |
| Low complexity EM-based decoding for OFDM systems with impulsive noise M Nassar, BL Evans 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals …, 2011 | 26 | 2011 |
| Variational Bayesian inference for forecasting hierarchical time series M Park, M Nassar International conference on machine learning (ICML), workshop on divergence …, 2014 | 25 | 2014 |
| Bayesian active learning for drug combinations M Park, M Nassar, H Vikalo IEEE transactions on biomedical engineering 60 (11), 3248-3255, 2013 | 24 | 2013 |
| Flexpoint: Predictive numerics for deep learning V Popescu, M Nassar, X Wang, E Tumer, T Webb 2018 IEEE 25th Symposium on Computer Arithmetic (ARITH), 1-4, 2018 | 23 | 2018 |
| Adaptive modulation and coding with frame size adjustment for power line communications (PLC) M Nassar, IH Kim, T Pande, AG Dabak US Patent 8,743,974, 2014 | 23 | 2014 |
| Methods and arrangements to quantize a neural network with machine learning S Majumdar, R Banner, M Nassar, L Storfer, A Agbaria, E Tumer, T Webb, ... US Patent 11,216,719, 2022 | 21 | 2022 |
Brian L. EvansEngineering Foundation Professor, ECE, WNCG, University of Texas at Austin在 ece.utexas.edu 的电子邮件经过验证
