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Biologically Plausible Sequence Learning with Spiking Neural Networks.

, , , and . AAAI, page 1316-1323. AAAI Press, (2020)

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Imputing missing values in sensor networks using sparse data representations., , , and . MSWiM, page 227-230. ACM, (2014)Deep Activity Recognition Models with Triaxial Accelerometers., , , , , and . AAAI Workshop: Artificial Intelligence Applied to Assistive Technologies and Smart Environments, volume WS-16-01 of AAAI Technical Report, AAAI Press, (2016)Biologically Plausible Sequence Learning with Spiking Neural Networks., , , and . AAAI, page 1316-1323. AAAI Press, (2020)A Blockchain-Based Approach for Collaborative Formalization of Mathematics and Programs., , , and . Blockchain, page 321-326. IEEE, (2021)Attention-based Graph Convolutional Network for Recommendation System., , , and . ICASSP, page 7560-7564. IEEE, (2019)Hypersurfaces and Their Singularities in Partial Correlation Testing, , , and . Foundations of Computational Mathematics, (2014)Fast Adaptation of Activity Sensing Policies in Mobile Devices., , , , and . CoRR, (2016)Capacity Pre-Log of Noncoherent SIMO Channels via Hironaka's Theorem, , , , , , and . CoRR, (2012)Rate-distortion Balanced Data Compression for Wireless Sensor Networks., , , and . CoRR, (2016)Biologically Plausible Sequence Learning with Spiking Neural Networks., , , and . CoRR, (2019)