9 citations · 25 across the 9 of their papers we have counts for
9 papers
Forecasting Unseen Points of Interest Visits Using Context and Proximity Priors
Ziyao Li, Shang-Ling Hsu, Cyrus Shahabi
Understanding human mobility behavior is crucial for numerous applications, including crowd management, location-based recommendations, and the estimation of pandemic spread. Machi…
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…
Deep Molecular Representation Learning via Fusing Physical and Chemical Information
Shuwen Yang, Ziyao Li, Guojie Song +1
Molecular representation learning is the first yet vital step in combining deep learning and molecular science. To push the boundaries of molecular representation learning, we pres…
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…