Jicong Fan

UniOD: A Universal Model for Outlier Detection across Diverse Domains

AutoDV: An End-to-End Deep Learning Model for High-Dimensional Data Visualization

Learnable Kernel Density Estimation for Graphs

Bridging Graph Worlds: Neural Approximation of Gromov-Wasserstein Distances

Training A Foundation Model to Represent Graphs as Vectors

Noise-Robust Density Estimation for Tabular Data Anomaly Detection

CLUBench: A Clustering Benchmark

Graph Minimum Factorization Distance and Its Application to Large-Scale Graph Data Clustering

Fairness-aware Anomaly Detection via Fair Projection

Self-Discriminative Modeling for Anomalous Graph Detection

AutoUAD: Hyper-parameter Optimization for Unsupervised Anomaly Detection

Explainable Graph Representation Learning via Graph Pattern Analysis

GraphProp: Training the Graph Foundation Models using Graph Properties

Subject Information Extraction for Novelty Detection with Domain Shifts