Adapting to the Stream: An Instance-Attention GNN Method for Irregular Multivariate Time Series Data
DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...
Swin-Chart is a Swin Transformer-based model for chart classification across various datasets. It achieved first place in the chart classification task at the ICDAR 2023 CHART Infographics competition ...
Lloyd’s Register (LR) and Latsco have successfully completed a proof-of-concept for a new standard in digital class assurance with data-driven surveys. This collaboration aims to demonstrate how ...
Abstract: Graph classification has always been a research hotspot in the field of graph neural networks and related areas. However, due to the complexity of graph data, finding a feasible algorithm ...
The World Bank's Papua New Guinea (PNG) Economic Update offers a comprehensive evaluation of the country's economy, highlighting the challenges and opportunities for sustainable growth, macro-fiscal ...
Electroencephalography (EEG) holds immense potential for decoding complex brain patterns associated with cognitive states and neurological conditions. In this paper, we propose an end-to-end framework ...
Department of Physics, University of Florida, Gainesville, Florida 32611, United States Center for Molecular Magnetic Quantum Materials, Gainesville, Florida 32611, United States Center for Molecular ...
Classic Graph Convolutional Networks (GCNs) often learn node representation holistically, which would ignore the distinct impacts from different neighbors when aggregating their features to update a ...
ABSTRACT: Aspect-oriented sentiment analysis is a meticulous sentiment analysis task that aims to analyse the sentiment polarity of specific aspects. Most of the current research builds graph ...
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