We aim to build a pre-trained Graph Neural Network (GNN) model on molecules without human annotations or prior knowledge. Although various attempts have been proposed to overcome limitations in ...
Abstract: Transformer-based architectures have gained popularity across various domains, including graph representation learning. However, selecting an optimal transformer configuration remains ...
Databricks provides tables designed for massive scale, enabling efficient storage and querying of tens of billions of triples with features like time travel No ETL or migration needed—just query your ...
We study two classes of summary-based cardinality estima tors that use statistics about input relations and joins of a small number of input relations: (i) optimistic estimators, which were defined in ...
Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...
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