7 citations · 8 across the 10 of their papers we have counts for
5 papers · 1 filter
RetroGEF: Dynamic Graph Edit Flow for Single-Step Retrosynthesis
Xiaozhuang Song, Xuemin Chen, Xinjian Zhao +2
Retrosynthesis enables the discovery of viable synthetic routes to target molecules. It plays a central role in modern drug discovery and materials design. Retrosynthesis involves…
HT-GNN: Hyper-Temporal Graph Neural Network for Customer Lifetime Value Prediction in Baidu Ads
Xiaohui Zhao, Xinjian Zhao, Jiahui Zhang +3
Lifetime value (LTV) prediction is crucial for news feed advertising, enabling platforms to optimize bidding and budget allocation for long-term revenue growth. However, it faces t…
Rethinking Spectral Augmentation for Contrast-based Graph Self-Supervised Learning
Xiangru Jian, Xinjian Zhao, Wei Pang +4
The recent surge in contrast-based graph self-supervised learning has prominently featured an intensified exploration of spectral cues. Spectral augmentation, which involves modify…
Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation
Xinjian Zhao, Liang Zhang, Yang Liu +2
Graph contrastive learning (GCL) has emerged as a pivotal technique in the domain of graph representation learning. A crucial aspect of effective GCL is the caliber of generated po…
Boosting Graph Pooling with Persistent Homology
Chaolong Ying, Xinjian Zhao, Tianshu Yu
Recently, there has been an emerging trend to integrate persistent homology (PH) into graph neural networks (GNNs) to enrich expressive power. However, naively plugging PH features…