3 citations · 3 across the 2 of their papers we have counts for
5 papers
HamNet: Conformation-Guided Molecular Representation with Hamiltonian Neural Networks
Ziyao Li, Shuwen Yang, Guojie Song +1
Well-designed molecular representations (fingerprints) are vital to combine medical chemistry and deep learning. Whereas incorporating 3D geometry of molecules (i.e. conformations)…
Learning Node Representations from Noisy Graph Structures
Junshan Wang, Ziyao Li, Qingqing Long +3
Learning low-dimensional representations on graphs has proved to be effective in various downstream tasks. However, noises prevail in real-world networks, which compromise networks…
A Novel User Representation Paradigm for Making Personalized Candidate Retrieval
Zheng Liu, Yu Xing, Jianxun Lian +3
Candidate retrieval is a fundamental issue in recommendation system. Given user's recommendation request, relevant candidates need to be retrieved in realtime for subsequent rankin…
GCN-LASE: Towards Adequately Incorporating Link Attributes in Graph Convolutional Networks
Ziyao Li, Liang Zhang, Guojie Song
Graph Convolutional Networks (GCNs) have proved to be a most powerful architecture in aggregating local neighborhood information for individual graph nodes. Low-rank proximities an…
SepNE: Bringing Separability to Network Embedding
Ziyao Li, Liang Zhang, Guojie Song
Many successful methods have been proposed for learning low dimensional representations on large-scale networks, while almost all existing methods are designed in inseparable proce…