19 citations · 32 across the 7 of their papers we have counts for
4 papers · 1 filter
Geometry-aware Line Graph Transformer Pre-training for Molecular Property Prediction
Peizhen Bai, Xianyuan Liu, Haiping Lu
Molecular property prediction with deep learning has gained much attention over the past years. Owing to the scarcity of labeled molecules, there has been growing interest in self-…
Interpretable bilinear attention network with domain adaptation improves drug-target prediction
Peizhen Bai, Filip Miljković, Bino John +1
Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model a…
PyKale: Knowledge-Aware Machine Learning from Multiple Sources in Python
Haiping Lu, Xianyuan Liu, Robert Turner +5
Machine learning is a general-purpose technology holding promises for many interdisciplinary research problems. However, significant barriers exist in crossing disciplinary boundar…
GripNet: Graph Information Propagation on Supergraph for Heterogeneous Graphs
Hao Xu, Shengqi Sang, Peizhen Bai +2
Heterogeneous graph representation learning aims to learn low-dimensional vector representations of different types of entities and relations to empower downstream tasks. Existing…