Search Results for author:
Found 8 papers, 3 papers with code
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic Graphs
We aim to predict future links within the dynamic graph while simultaneously providing causal explanations for these predictions.
A parameter-free clustering algorithm for missing datasets
Missing datasets, in which some objects have missing values in certain dimensions, are prevalent in the Real-world.
A variational autoencoder-based nonnegative matrix factorisation model for deep dictionary learning
Construction of dictionaries using nonnegative matrix factorisation (NMF) has extensive applications in signal processing and machine learning.
Position-enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations
PTGCN models the sequential patterns and temporal dynamics between user-item interactions by defining a position-enhanced and time-aware graph convolution operation and learning the dynamic representations of users and items simultaneously on the bipartite graph with a self-attention aggregator.
High-Order Information Matters: Learning Relation and Topology for Occluded Person Re-Identification
When aligning two groups of local features from two images, we view it as a graph matching problem and propose a cross-graph embedded-alignment (CGEA) layer to jointly learn and embed topology information to local features, and straightly predict similarity score.
Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud
A novel approach is proposed to achieve cost-effective big data clustering in the cloud.
Comment on "Clustering by fast search and find of density peaks"
For any data set to be clustered, the most reasonable value of d_c can be objectively calculated from the data set by using our proposed method.
A Novel Method to Extract Rocks from Mars Images
In this paper, a novel method is proposed to extract rocks from Martian surface images by using 8 data field.
