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Found 3 papers, 2 papers with code
Contextual Unsupervised Outlier Detection in Sequences
This work proposes an unsupervised learning framework for trajectory (sequence) outlier detection that combines ranking tests with user sequence models.
Deep Lifetime Clustering
The goal of lifetime clustering is to develop an inductive model that maps subjects into $K$ clusters according to their underlying (unobserved) lifetime distribution.
Are Graph Neural Networks Miscalibrated?
Graph Neural Networks (GNNs) have proven to be successful in many classification tasks, outperforming previous state-of-the-art methods in terms of accuracy.
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