54 citations · 105 across the 4 of their papers we have counts for
6 papers
KEPLA: A Knowledge-Enhanced Deep Learning Framework for Accurate Protein-Ligand Binding Affinity Prediction
Han Liu, Keyan Ding, Peilin Chen +4
Accurate prediction of protein-ligand binding affinity is critical for drug discovery. While recent deep learning approaches have demonstrated promising results, they often rely so…
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
Han Liu, Yinwei Wei, Fan Liu +3
Multimodal information (e.g., visual, acoustic, and textual) has been widely used to enhance representation learning for micro-video recommendation. For integrating multimodal info…
MMGRec: Multimodal Generative Recommendation with Transformer Model
Han Liu, Yinwei Wei, Xuemeng Song +3
Multimodal recommendation aims to recommend user-preferred candidates based on her/his historically interacted items and associated multimodal information. Previous studies commonl…
HS-GCN: Hamming Spatial Graph Convolutional Networks for Recommendation
Han Liu, Yinwei Wei, Jianhua Yin +1
An efficient solution to the large-scale recommender system is to represent users and items as binary hash codes in the Hamming space. Towards this end, existing methods tend to co…
Review Polarity-wise Recommender
Han Liu, Yangyang Guo, Jianhua Yin +2
Utilizing review information to enhance recommendation, the de facto review-involved recommender systems, have received increasing interests over the past few years. Thereinto, one…
Discrete Factorization Machines for Fast Feature-based Recommendation
Han Liu, Xiangnan He, Fuli Feng +3
User and item features of side information are crucial for accurate recommendation. However, the large number of feature dimensions, e.g., usually larger than 10^7, results in expe…