Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
This course is available on the MSc in Data Science, MSc in Geographic Data Science, MSc in Health Data Science, MSc in Operations Research & Analytics, MSc in Quantitative Methods for Risk Management ...
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 ...
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