8 papers
PromptDyG: Test-Time Prompt Adaptation on Dynamic Graphs
Guoguo Ai, Chaoxi Niu, Hui Yan +3
Activities in numerous evolving systems can be represented as dynamic graphs in snapshot form at different time intervals, i.e., discrete-time dynamic graphs (DTDGs). Existing meth…
WaveTuner: Comprehensive Wavelet Subband Tuning for Time Series Forecasting
Yubo Wang, Hui He, Chaoxi Niu +1
Due to the inherent complexity, temporal patterns in real-world time series often evolve across multiple intertwined scales, including long-term periodicity, short-term fluctuation…
Reprogramming Vision Foundation Models for Spatio-Temporal Forecasting
Changlu Chen, Yanbin Liu, Chaoxi Niu +2
Foundation models have achieved remarkable success in natural language processing and computer vision, demonstrating strong capabilities in modeling complex patterns. While recent…
Zero-shot Generalist Graph Anomaly Detection with Unified Neighborhood Prompts
Chaoxi Niu, Hezhe Qiao, Changlu Chen +2
Graph anomaly detection (GAD), which aims to identify nodes in a graph that significantly deviate from normal patterns, plays a crucial role in broad application domains. However,…
AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection
Hezhe Qiao, Chaoxi Niu, Ling Chen +1
Graph anomaly detection (GAD) aims to identify abnormal nodes that differ from the majority of the nodes in a graph, which has been attracting significant attention in recent years…
Hierarchical Consensus Network for Multiview Feature Learning
Chengwei Xia, Chaoxi Niu, Kun Zhan
Multiview feature learning aims to learn discriminative features by integrating the distinct information in each view. However, most existing methods still face significant challen…