50 citations · 69 across the 12 of their papers we have counts for
5 papers · 1 filter
Deep Reinforcement Learning for Entity Alignment
Lingbing Guo, Yuqiang Han, Qiang Zhang +1
Embedding-based methods have attracted increasing attention in recent entity alignment (EA) studies. Although great promise they can offer, there are still several limitations. The…
On Exploring Pose Estimation as an Auxiliary Learning Task for Visible-Infrared Person Re-identification
Yunqi Miao, Nianchang Huang, Xiao Ma +2
Visible-infrared person re-identification (VI-ReID) has been challenging due to the existence of large discrepancies between visible and infrared modalities. Most pioneering approa…
Prompt-Guided Injection of Conformation to Pre-trained Protein Model
Qiang Zhang, Zeyuan Wang, Yuqiang Han +3
Pre-trained protein models (PTPMs) represent a protein with one fixed embedding and thus are not capable for diverse tasks. For example, protein structures can shift, namely protei…
Knowledge-informed Molecular Learning: A Survey on Paradigm Transfer
Yin Fang, Zhuo Chen, Xiaohui Fan +1
Machine learning, notably deep learning, has significantly propelled molecular investigations within the biochemical sphere. Traditionally, modeling for such research has centered…
OntoProtein: Protein Pretraining With Gene Ontology Embedding
Ningyu Zhang, Zhen Bi, Xiaozhuan Liang +6
Self-supervised protein language models have proved their effectiveness in learning the proteins representations. With the increasing computational power, current protein language…