In this correspondence, we study deep learning methods for CSI extrapolation in high-resolution FAS with less complexity and greater generalization ability. In so doing, we then contrive a customized ...

To address this issue, we design a novel network architecture for multi-user time-frequency-space joint channel extrapolation that integrates a temporal graph convolutional network (TGCN) and a ...

The prediction of the projected density of states (PDOS) in materials has traditionally relied on deep learning models based on graph convolutional networks (GCN) and Graph Attention Networks (GAT).

We introduce the Geometric-DESIGNN method, which integrates Geometric Guidance with Directed Electrostatics Strategy within a Graph Neural Network framework to predict the stable configuration of ...

Working in tandem, a quantum computer and a supercomputer modelled the behaviour of several molecules, paving the way for ...

Every year, more than one million scientific articles are published in the life sciences. Two-thirds of them include ...

Researchers at Colorado State University have developed a new photoredox catalysis system that uses visible light mimicking ...

We rarely think about how liquids flow—why honey is thick, water is thin or how molten plastic moves through machines. But ...

The precursors of heavy elements might arise in the plasma underbellies of swollen stars or in smoldering stellar corpses.

Assessing the distribution of a medication in the brain is critical for the treatment of a vast range of neurological ...

Centrosymmetric crystals have always absorbed equal amounts of left- and right-handed circularly polarized light—until now ...