891 citations · 1.4k across the 37 of their papers we have counts for
12 papers · 1 filter
Cross-Domain Graph Anomaly Detection via Anomaly-aware Contrastive Alignment
Qizhou Wang, Guansong Pang, Mahsa Salehi +2
Cross-domain graph anomaly detection (CD-GAD) describes the problem of detecting anomalous nodes in an unlabelled target graph using auxiliary, related source graphs with labelled…
Diversity Enhanced Active Learning with Strictly Proper Scoring Rules
Wei Tan, Lan Du, Wray Buntine
We study acquisition functions for active learning (AL) for text classification. The Expected Loss Reduction (ELR) method focuses on a Bayesian estimate of the reduction in classif…
The Neglected Sibling: Isotropic Gaussian Posterior for VAE
Lan Zhang, Wray Buntine, Ehsan Shareghi
Deep generative models have been widely used in several areas of NLP, and various techniques have been proposed to augment them or address their training challenges. In this paper,…
Hands-on Bayesian Neural Networks -- a Tutorial for Deep Learning Users
Laurent Valentin Jospin, Wray Buntine, Farid Boussaid +2
Modern deep learning methods constitute incredibly powerful tools to tackle a myriad of challenging problems. However, since deep learning methods operate as black boxes, the uncer…
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…