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Sequence Generation via Subsequence Similarity: Theory and Application to UAV Identification
The ability to generate synthetic sequences is crucial for a wide range of applications, and recent advances in deep learning architectures and generative frameworks have greatly facilitated this process.
Time Series Synthesis via Multi-scale Patch-based Generation of Wavelet Scalogram
A framework is proposed for the unconditional generation of synthetic time series based on learning from a single sample in low-data regime case.
IGANI: Iterative Generative Adversarial Networks for Imputation with Application to Traffic Data
Increasing use of sensor data in intelligent transportation systems calls for accurate imputation algorithms that can enable reliable traffic management in the occasional absence of data.
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