Peptides designed by artificial intelligence restrict both drug-resistant bacteria and rapidly evolving viruses.

Abstract: In recent years, convolutional neural networks (CNNs) have been impressive due ... Therefore, this paper proposes a hybrid CNN-GCN network (HCGN) for hyperspectral image classification.

Compared with machine learning and deep learning technologies, graph convolutional neural network (GCN) achieves better detection results of malicious traffic due to additional consideration of the ...

STM-GCN: a spatiotemporal multi-graph convolutional network for pedestrian trajectory prediction[J]. The Journal of Supercomputing, 2023. paper code 8-Yang Z, Pang C, Zeng X. Trajectory Forecasting ...

A research team led by Prof. Gao Xiaoming from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences ...

Physics-informed neural networks were tested for their capabilities in predicting concentration profiles in gradient liquid ...

Nikita Belyakov and Svetlana Illarionova, researchers from the Skoltech AI Center, presented a new method for semantic segmentation of multispectral data, which can be used to recognize clouds, ...

Binary neutron star mergers occur millions of light-years away from Earth. Interpreting the gravitational waves they produce presents a major challenge for traditional data-analysis methods. These ...