8 citations · 21 across the 7 of their papers we have counts for
7 papers
Enhancing Graph Representation Learning with Localized Topological Features
Zuoyu Yan, Qi Zhao, Ze Ye +5
Representation learning on graphs is a fundamental problem that can be crucial in various tasks. Graph neural networks, the dominant approach for graph representation learning, are…
Cycle Invariant Positional Encoding for Graph Representation Learning
Zuoyu Yan, Tengfei Ma, Liangcai Gao +3
Cycles are fundamental elements in graph-structured data and have demonstrated their effectiveness in enhancing graph learning models. To encode such information into a graph learn…
Attention Hijacking in Trojan Transformers
Weimin Lyu, Songzhu Zheng, Tengfei Ma +2
Trojan attacks pose a severe threat to AI systems. Recent works on Transformer models received explosive popularity and the self-attentions are now indisputable. This raises a cent…
A Study of the Attention Abnormality in Trojaned BERTs
Weimin Lyu, Songzhu Zheng, Tengfei Ma +1
Trojan attacks raise serious security concerns. In this paper, we investigate the underlying mechanism of Trojaned BERT models. We observe the attention focus drifting behavior of…
Neural Approximation of Graph Topological Features
Zuoyu Yan, Tengfei Ma, Liangcai Gao +3
Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods. However, computing extended persistent ho…
Cycle Representation Learning for Inductive Relation Prediction
Zuoyu Yan, Tengfei Ma, Liangcai Gao +2
In recent years, algebraic topology and its modern development, the theory of persistent homology, has shown great potential in graph representation learning. In this paper, based…
Link Prediction with Persistent Homology: An Interactive View
Zuoyu Yan, Tengfei Ma, Liangcai Gao +2
Link prediction is an important learning task for graph-structured data. In this paper, we propose a novel topological approach to characterize interactions between two nodes. Our…