Researchers from Arizona State University and Intel Foundry have published “Graph Attention-Based Virtual Metrology for Film ...

PromptSE uses structured LLM prompting to generate pharmacologically relevant side-effect representations, then feeds them ...

Abstract: Methane is one of the most dangerous gases produced in the process of coal mining. Because of its flammable and explosive characteristics, it has seriously threatened the life and property ...

Graph Convolutional Networks (GCNs) are widely applied for spatial domain identification in spatial transcriptomics (ST), where node representations are learned by aggregating information from ...

Accurate prediction of protein-protein interactions (PPIs) is crucial for understanding cellular functions and advancing the development of drugs. While existing in-silico methods leverage direct ...

Abstract: Graph Convolutional Network (GCN) has been widely applied in mechanical fault diagnosis due to its ability to extract features from data in non-Euclidean spaces. However, the local ...

ABSTRACT: Convolutional auto-encoders have shown their remarkable performance in stacking deep convolutional neural networks for classifying image data during the past several years. However, they are ...

The repository of GALG, a graph-based artificial intelligence approach to link addresses for user tracking on TLS encrypted traffic. The work has been accepted as ECML/PKDD 2022 accepted Paper.