Decision-making inherently involves cause–effect relationships that introduce causal challenges. We argue that reliable algorithms for decision-making need to build upon causal reasoning.

i.e. a modified graph neural network (GNN) model. In brief, scDeepSort was constructed based on our weighted GNN framework and was then learned in two embedded high-quality scRNA-seq atlases ...

Abstract: Timed event graphs (TEGs) and timed weighted event graphs (TWEGs), which have multiple arc cardinalities, have been widely used for automated production systems such as robotic work cells or ...

Our approach is to seek the optimal partitioning of 3D space into two regions labeled as "object" and "empty" under ... can be obtained as the minimum cut solution of a weighted graph.

3. Graph Neural Networks GNNs have a broad range of uses in various domains due to the prevalence of graph-structured data, where the lack of an Euclidean structure makes it challenging to use DNNs in ...