Neural networks in wireless networks: Techniques, applications and guidelines N Ahad, J Qadir, N Ahsan Journal of network and computer applications 68, 1-27, 2016 | 82 | 2016 |
Building programmable wireless networks: an architectural survey J Qadir, N Ahmed, N Ahad EURASIP Journal on Wireless Communications and Networking 2014, 1-31, 2014 | 48 | 2014 |
SDNs, clouds, and big data: new opportunities J Qadir, N Ahad, E Mushtaq, M Bilal 2014 12th International Conference on Frontiers of Information Technology, 28-33, 2014 | 25 | 2014 |
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time F Zhu, A Sedler, HA Grier, N Ahad, M Davenport, M Kaufman, ... Advances in Neural Information Processing Systems 34, 2331-2345, 2021 | 14 | 2021 |
Validating a wheelchair in-seat activity tracker N Ahad, SE Sonenblum, MA Davenport, S Sprigle Assistive Technology 34 (5), 588-598, 2022 | 10 | 2022 |
Semi-supervised sequence classification through change point detection N Ahad, MA Davenport AAAI Conf. on Artificial Intelligenec (AAAI-21), 2021 | 7 | 2021 |
Learning sinkhorn divergences for supervised change point detection N Ahad, EL Dyer, KB Hengen, Y Xie, MA Davenport arXiv preprint arXiv:2202.04000, 2022 | 4 | 2022 |
Mtneuro: A benchmark for evaluating representations of brain structure across multiple levels of abstraction J Quesada, L Sathidevi, R Liu, N Ahad, J Jackson, M Azabou, J Xiao, ... Advances in neural information processing systems 35, 5299-5314, 2022 | 3 | 2022 |
Learning behavior representations through multi-timescale bootstrapping M Azabou, M Mendelson, M Sorokin, S Thakoor, N Ahad, C Urzay, ... arXiv preprint arXiv:2206.07041, 2022 | 3 | 2022 |
Data-adaptive symmetric CUSUM for sequential change detection N Ahad, MA Davenport, Y Xie Sequential Analysis 43 (1), 1-27, 2024 | 1 | 2024 |
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis M Azabou, M Mendelson, N Ahad, M Sorokin, S Thakoor, C Urzay, ... CVPR 2022, Workshop on Multi-Agent Behavior, 2023 | 1 | 2023 |
Semi-supervised framework for efficient time-series ordinal classification L Tong, T Mizoguchi, Z Chen, W Cheng, H Chen, N Ahad US Patent App. 18/545,055, 2024 | | 2024 |
Semi-supervised framework for efficient time-series ordinal classification L Tong, T Mizoguchi, Z Chen, W Cheng, H Chen, N Ahad US Patent App. 18/545,025, 2024 | | 2024 |
Semi-supervised framework for efficient time-series ordinal classification L Tong, T Mizoguchi, Z Chen, W Cheng, H Chen, N Ahad US Patent App. 18/152,238, 2023 | | 2023 |
Ordinal classification through network decomposition T Mizoguchi, L Tong, Z Chen, W Cheng, H Chen, N Ahad US Patent App. 17/896,747, 2023 | | 2023 |
Active learning for time instant classification N Ahad, N Nadagouda, EL Dyer, MA Davenport ICML 2023, workshop on data-centric machine learning research, 2023 | | 2023 |
Detecting change points in neural population activity with contrastive metric learning C Urzay, N Ahad, M Azabou, A Schneider, G Atmakuri, KB Hengen, ... 11th International IEEE/EMBS Conference on Neural Engineering (NER), 2023 | | 2023 |
Delta Distancing: A Lifting Approach to Localizing Items from User Comparisons AD McRae, A Xu, J Jin, N Nadagouda, N Ahad, P Guan, S Karnik, ... ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | | 2022 |