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Journal Articles
- 2016
[j2]Nauman Ahad, Junaid Qadir
, Nasir Ahsan:
Neural networks in wireless networks: Techniques, applications and guidelines. J. Netw. Comput. Appl. 68: 1-27 (2016)- 2014
- [j1]Junaid Qadir, Nadeem Ahmed, Nauman Ahad:
Building programmable wireless networks: an architectural survey. EURASIP J. Wirel. Commun. Netw. 2014: 172 (2014)
Conference and Workshop Papers
- 2023
- [c7]Carolina Urzay, Nauman Ahad, Mehdi Azabou, Aidan Schneider, Geethika Atamkuri, Keith B. Hengen, Eva L. Dyer:
Detecting change points in neural population activity with contrastive metric learning. NER 2023: 1-4 - [c6]Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer:
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. NeurIPS 2023 - 2022
- [c5]Andrew D. McRae, Austin Xu, Jihui Jin, Namrata Nadagouda, Nauman Ahad, Peimeng Guan, Santhosh Karnik, Mark A. Davenport:
Delta Distancing: A Lifting Approach to Localizing Items from User Comparisons. ICASSP 2022: 5558-5562 - [c4]Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William R. Gray Roncal, Erik C. Johnson, Eva L. Dyer:
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. NeurIPS 2022 - 2021
- [c3]Nauman Ahad, Mark A. Davenport:
Semi-supervised Sequence Classification through Change Point Detection. AAAI 2021: 6574-6581 - [c2]Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath:
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. NeurIPS 2021: 2331-2345 - 2014
- [c1]Junaid Qadir, Nauman Ahad, Erum Mushtaq, Muhammad Bilal:
SDNs, Clouds, and Big Data: New Opportunities. FIT 2014: 28-33
Informal and Other Publications
- 2023
- [i7]Jorge Quesada, Lakshmi Sathidevi, Ran Liu, Nauman Ahad, Joy M. Jackson, Mehdi Azabou, Jingyun Xiao, Christopher Liding, Matthew Jin, Carolina Urzay, William R. Gray Roncal, Erik C. Johnson, Eva L. Dyer:
MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction. CoRR abs/2301.00345 (2023) - [i6]Mehdi Azabou, Michael Mendelson, Nauman Ahad, Maks Sorokin, Shantanu Thakoor, Carolina Urzay, Eva L. Dyer:
Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis. CoRR abs/2303.08811 (2023) - 2022
- [i5]Nauman Ahad, Eva L. Dyer, Keith B. Hengen, Yao Xie, Mark A. Davenport:
Learning Sinkhorn divergences for supervised change point detection. CoRR abs/2202.04000 (2022) - [i4]Mehdi Azabou, Michael Mendelson, Maks Sorokin, Shantanu Thakoor, Nauman Ahad, Carolina Urzay, Eva L. Dyer:
Learning Behavior Representations Through Multi-Timescale Bootstrapping. CoRR abs/2206.07041 (2022) - 2021
- [i3]Feng Zhu, Andrew R. Sedler, Harrison A. Grier, Nauman Ahad, Mark A. Davenport, Matthew T. Kaufman, Andrea Giovannucci, Chethan Pandarinath:
Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time. CoRR abs/2111.00070 (2021) - 2020
- [i2]Nauman Ahad, Mark A. Davenport:
Semi-supervised sequence classification through change point detection. CoRR abs/2009.11829 (2020) - 2013
- [i1]Junaid Qadir, Nadeem Ahmed, Nauman Ahad:
Building Programmable Wireless Networks: An Architectural Survey. CoRR abs/1310.0251 (2013)
Coauthor Index
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