STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
Abstract: Conversational Aspect-based Sentiment Quadruple Analysis (DiaASQ) is a fine-grained sentiment analysis task that aims at extracting targets, aspects, opinions, and sentiments from multi-turn ...
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