891 citations · 1.4k across the 37 of their papers we have counts for
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Gaussian Embedding of Large-scale Attributed Graphs
Bhagya Hettige, Yuan-Fang Li, Weiqing Wang +1
Graph embedding methods transform high-dimensional and complex graph contents into low-dimensional representations. They are useful for a wide range of graph analysis tasks includi…
Structural and Temporal Representation Learning of Electronic Medical Records
Bhagya Hettige, Yuan-Fang Li, Weiqing Wang +2
Electronic medical record (EMR) data contains historical sequences of visits of patients, and each visit contains rich information, such as patient demographics, hospital utilisati…
LoRMIkA: Local rule-based model interpretability with k-optimal associations
Dilini Rajapaksha, Christoph Bergmeir, Wray Buntine
As we rely more and more on machine learning models for real-life decision-making, being able to understand and trust the predictions becomes ever more important. Local explainer m…
Variational Autoencoders for Sparse and Overdispersed Discrete Data
He Zhao, Piyush Rai, Lan Du +2
Many applications, such as text modelling, high-throughput sequencing, and recommender systems, require analysing sparse, high-dimensional, and overdispersed discrete (count-valued…