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21 papers · 1 filter
Absolute indices for determining compactness, separability and number of clusters
Adil M. Bagirov, Ramiz M. Aliguliyev, Nargiz Sultanova +1
Finding "true" clusters in a data set is a challenging problem. Clustering solutions obtained using different models and algorithms do not necessarily provide compact and well-sepa…
Graph Learning
Feng Xia, Ciyuan Peng, Jing Ren +5
Graph learning has rapidly evolved into a critical subfield of machine learning and artificial intelligence (AI). Its development began with early graph-theoretic methods, gaining…
Refined Causal Graph Structure Learning via Curvature for Brain Disease Classification
Falih Gozi Febrinanto, Adonia Simango, Chengpei Xu +4
Graph neural networks (GNNs) have been developed to model the relationship between regions of interest (ROIs) in brains and have shown significant improvement in detecting brain di…
EAGLE: Contrastive Learning for Efficient Graph Anomaly Detection
Jing Ren, Mingliang Hou, Zhixuan Liu +1
Graph anomaly detection is a popular and vital task in various real-world scenarios, which has been studied for several decades. Recently, many studies extending deep learning-base…
Graph Transformers: A Survey
Ahsan Shehzad, Feng Xia, Shagufta Abid +4
Graph transformers are a recent advancement in machine learning, offering a new class of neural network models for graph-structured data. The synergy between transformers and graph…
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
Xin Chen, Mingliang Hou, Tao Tang +2
With the arrival of the big data era, mobility profiling has become a viable method of utilizing enormous amounts of mobility data to create an intelligent transportation system. M…