Neural networks in wireless networks: Techniques, applications and guidelines von Ahad, Nauman, Qadir, Junaid, Ahsan, Nasir

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Building programmable wireless networks: an architectural survey von Qadir, Junaid, Ahmed, Nadeem, Ahad, Nauman

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Building programmable wireless networks: an architectural survey: Doc 990 von Qadir, Junaid, Ahmed, Nadeem, Ahad, Nauman

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Building Programmable Wireless Networks: An Architectural Survey von Qadir, Junaid, Ahmed, Nadeem, Nauman Ahad

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Data-Adaptive Symmetric CUSUM for Sequential Change Detection von Ahad, Nauman, Davenport, Mark A, Xie, Yao

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Semi-supervised sequence classification through change point detection von Ahad, Nauman, Davenport, Mark A

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Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis von Azabou, Mehdi, Mendelson, Michael, Ahad, Nauman, Sorokin, Maks, Thakoor, Shantanu, Urzay, Carolina, Dyer, Eva L

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Learning Behavior Representations Through Multi-Timescale Bootstrapping von Azabou, Mehdi, Mendelson, Michael, Sorokin, Maks, Thakoor, Shantanu, Ahad, Nauman, Urzay, Carolina, Dyer, Eva L

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Data-Adaptive Symmetric CUSUM for Sequential Change Detection von Nauman Ahad, Davenport, Mark A, Xie, Yao

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Learning Sinkhorn divergences for supervised change point detection von Ahad, Nauman, Dyer, Eva L, Hengen, Keith B, Xie, Yao, Davenport, Mark A

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Semi-supervised sequence classification through change point detection von Nauman Ahad, Davenport, Mark A

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von CHENG, Wei, CHEN, Haifeng, TONG, Liang, AHAD, Nauman, MIZOGUCHI, Takehiko, CHEN, Zhengzhang

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Deep inference of latent dynamics with spatio-temporal super-resolution using selective backpropagation through time von Zhu, Feng, Sedler, Andrew R, Grier, Harrison A, Ahad, Nauman, Davenport, Mark A, Kaufman, Matthew T, Giovannucci, Andrea, Pandarinath, Chethan

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von Chen, Zhengzhang, Ahad, Nauman, Mizoguchi, Takehiko, Tong, Liang, Cheng, Wei, Chen, Haifeng

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MTNeuro: A Benchmark for Evaluating Representations of Brain Structure Across Multiple Levels of Abstraction von Quesada, Jorge, Sathidevi, Lakshmi, Liu, Ran, Ahad, Nauman, Jackson, Joy M, Azabou, Mehdi, Xiao, Jingyun, Liding, Christopher, Jin, Matthew, Urzay, Carolina, Gray-Roncal, William, Johnson, Erik C, Dyer, Eva L

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von Chen, Zhengzhang, Ahad, Nauman, Mizoguchi, Takehiko, Tong, Liang, Cheng, Wei, Chen, Haifeng

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von Chen, Zhengzhang, Ahad, Nauman, Mizoguchi, Takehiko, Tong, Liang, Cheng, Wei, Chen, Haifeng

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von CHENG, Wei, CHEN, Haifeng, TONG, Liang, AHAD, Nauman, MIZOGUCHI, Takehiko, CHEN, Zhengzhang

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SEMI-SUPERVISED FRAMEWORK FOR EFFICIENT TIME-SERIES ORDINAL CLASSIFICATION von Chen, Zhengzhang, Ahad, Nauman, Mizoguchi, Takehiko, Tong, Liang, Cheng, Wei, Chen, Haifeng

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Relax, it doesn't matter how you get there: A new self-supervised approach for multi-timescale behavior analysis von Azabou, Mehdi, Mendelson, Michael, Nauman Ahad, Sorokin, Maks, Thakoor, Shantanu, Urzay, Carolina, Dyer, Eva L

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