The key to the success of few-shot segmentation (FSS) lies in how to
eff...
Mining cohesive subgraphs from a graph is a fundamental problem in graph...
Road network is a critical infrastructure powering many applications
inc...
Road extraction is a process of automatically generating road maps mainl...
Approximate K nearest neighbor (AKNN) search is a fundamental and challe...
Computing the densest subgraph is a primitive graph operation with criti...
When users move in a physical space (e.g., an urban space), they would h...
Unsupervised region representation learning aims to extract dense and
ef...
As the popularity of graph data increases, there is a growing need to co...
Detecting anomalous trajectories has become an important task in many
lo...
Enumerating maximal k-biplexes (MBPs) of a bipartite graph has been used...
Open Information Extraction (OpenIE) facilitates domain-independent disc...
As a fundamental component in location-based services, inferring the
rel...
Mining maximal subgraphs with cohesive structures from a bipartite graph...
Learned indices have been proposed to replace classic index structures l...
Similar trajectory search is a fundamental problem and has been well stu...
Forecasting the motion of surrounding dynamic obstacles (vehicles, bicyc...
Recently, the topic of graph representation learning has received plenty...