Abstract: Revealing the latent low-dimensional geometric structure of high-dimensional data is a crucial task in unsupervised representation learning. Traditional manifold learning, as a typical ...

Abstract: Energy-efficiency (EE) is a critical metric within wireless optimization. Power control over fading channels is considered as a promising EE-improving technique, but requires optimization of ...

When and where the next large earthquake will strike remains one of the most difficult questions in geoscience. Researchers ...

In this work, we propose an unsupervised deep learning model to address multi-focus image fusion problem. First, we train an encoder-decoder architecture in unsupervised manner to acquire deep feature ...

Designing an unsupervised image denoising approach in practical applications is a challenging task due to the complicated data acquisition process. In the realworld case, the noise distribution is so ...

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability ...

A steer-by-wire bicycle reliably distinguishes between cornering and unstable riding conditions, enhancing riding safety.

Howdy, pards, here's a quick roundup of the week's science news: Moose, previously thought to be a transplanted species, are ...

A study published in Nature Physics provides new molecular-level evidence from simulations that liquid water is not a single ...

ENVIRONMENT: An Investment company is searching for a talented and driven Data Scientist to join their innovative and growing team based in Durbanville, Cape Town. This is an exciting opportunity to ...

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...

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