Abstract: Spectrum prediction is challenging due to its multi-dimension, complex inherent dependency, and heterogeneity among the spectrum data. In this paper, we first propose a stacked autoencoder ...

Autonomous vehicles are essentially data centers on wheels. Between self-driving algorithms and high-definition mapping, the demand for instant processing at the network edge is exploding. But here is ...

well there are some awesome-lists for word embeddings and sentence embeddings, but all of them are outdated and more importantly incomplete this repo will also be incomplete, but I'll try my best to ...

The rapid growth of unlabeled time-series data in domains such as wireless communications, radar, biomedical engineering, and the Internet of Things (IoT) has driven advancements in unsupervised ...

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...

In response to the issue of massive data volume generated by magnetic flux leakage (MFL) non-destructive testing in oil and gas pipelines, an intelligent data compression method based on a targeted ...

Drilling incident predictors (DIP) anticipate drilling incidents which can lead to non-productive time. Researchers at the University of Texas at Austin produced data-driven and hybrid data-physics ...

Clone the repository: bash git clone https://github.com/VIVEKGANGA/ML-DL-Algorithms-From-Scratch.git Explore Algorithms: Each file contains implementations of core ...

Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai200237, China ...

Abstract: Visible light communication (VLC) is a relatively new wireless communication technology that allows for high data rate transfer. Because of its capability to enable high-speed transmission ...

Automatic detection and alarm of abnormal electrocardiogram (ECG) events play an important role in an ECG monitor system; however, popular classification models based on supervised learning fail to ...

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