This paper introduces a refined graph encoder embedding method, enhancing the original graph encoder embedding through linear transformation, self-training, and hidden community recovery within ...
This project implements a Variational Autoencoder (VAE) for image generation. Unlike standard autoencoders, VAE learns a probabilistic latent space by encoding images to a distribution and sampling ...
BREMEN, Germany — The European Space Agency member states have approved a record-breaking budget for the agency's next three-year period, including an increase in funding for science exploration and ...
LatentMAS is a multi-agent reasoning framework that moves agent collaboration from token space into the model’s latent space. Instead of producing long textual reasoning traces, agents communicate by ...
Abstract: During the period of superior solar conjunction, the deep-space channel suffers from solar scintillation and large Doppler shifts, leading to highly time-varying communication links. To ...
Abstract: Deep neural networks (DNNs) have achieved remarkable progress in remote sensing image (RSI) analysis, yet their vulnerability to subtle adversarial perturbations poses a critical threat to ...
As more nations and private companies turn their sights toward the Moon, the region between Earth and lunar orbit has become a frontier of opportunity, risk, and strategic competition. Now, the U.S.
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