2 citations · 2 across the 5 of their papers we have counts for
5 papers
On Structural Expressive Power of Graph Transformers
Wenhao Zhu, Tianyu Wen, Guojie Song +2
Graph Transformer has recently received wide attention in the research community with its outstanding performance, yet its structural expressive power has not been well analyzed. I…
Dual Intent Enhanced Graph Neural Network for Session-based New Item Recommendation
Di Jin, Luzhi Wang, Yizhen Zheng +5
Recommender systems are essential to various fields, e.g., e-commerce, e-learning, and streaming media. At present, graph neural networks (GNNs) for session-based recommendations n…
Hierarchical Transformer for Scalable Graph Learning
Wenhao Zhu, Tianyu Wen, Guojie Song +2
Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning…
Equivalent Distance Geometry Error for Molecular Conformation Comparison
Shuwen Yang, Tianyu Wen, Ziyao Li +1
Straight-forward conformation generation models, which generate 3-D structures directly from input molecular graphs, play an important role in various molecular tasks with machine…
Stepping Back to SMILES Transformers for Fast Molecular Representation Inference
Wenhao Zhu, Ziyao Li, Lingsheng Cai +1
In the intersection of molecular science and deep learning, tasks like virtual screening have driven the need for a high-throughput molecular representation generator on large chem…