1.7k citations · 3.8k across the 62 of their papers we have counts for
69 papers
FraudFox: Adaptable Fraud Detection in the Real World
Matthew Butler, Yi Fan, Christos Faloutsos
The proposed method (FraudFox) provides solutions to adversarial attacks in a resource constrained environment. We focus on questions like the following: How suspicious is `Smith',…
TouchUp-G: Improving Feature Representation through Graph-Centric Finetuning
Jing Zhu, Xiang Song, Vassilis N. Ioannidis +2
How can we enhance the node features acquired from Pretrained Models (PMs) to better suit downstream graph learning tasks? Graph Neural Networks (GNNs) have become the state-of-the…
Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs
Zijie Huang, Daheng Wang, Binxuan Huang +8
Knowledge graph embeddings (KGE) have been extensively studied to embed large-scale relational data for many real-world applications. Existing methods have long ignored the fact ma…
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang +6
How can we learn effective node representations on textual graphs? Graph Neural Networks (GNNs) that use Language Models (LMs) to encode textual information of graphs achieve state…
ExplainFix: Explainable Spatially Fixed Deep Networks
Alex Gaudio, Christos Faloutsos, Asim Smailagic +2
Is there an initialization for deep networks that requires no learning? ExplainFix adopts two design principles: the "fixed filters" principle that all spatial filter weights of co…
PaGE-Link: Path-based Graph Neural Network Explanation for Heterogeneous Link Prediction
Shichang Zhang, Jiani Zhang, Xiang Song +4
Transparency and accountability have become major concerns for black-box machine learning (ML) models. Proper explanations for the model behavior increase model transparency and he…