7 citations · 19 across the 5 of their papers we have counts for
5 papers
PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction
Yuancheng Sun, Yimeng Chen, Weizhi Ma +5
Molecular property prediction is essential for drug discovery. In recent years, deep learning methods have been introduced to this area and achieved state-of-the-art performances.…
A Survey on Dropout Methods and Experimental Verification in Recommendation
Yangkun Li, Weizhi Ma, Chong Chen +4
Overfitting is a common problem in machine learning, which means the model too closely fits the training data while performing poorly in the test data. Among various methods of cop…
A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing
Bin Hao, Min Zhang, Weizhi Ma +5
Data plays a vital role in machine learning studies. In the research of recommendation, both user behaviors and side information are helpful to model users. So, large-scale real sc…
Neural Logic Reasoning
Shaoyun Shi, Hanxiong Chen, Weizhi Ma +3
Recent years have witnessed the success of deep neural networks in many research areas. The fundamental idea behind the design of most neural networks is to learn similarity patter…
Jointly Learning Explainable Rules for Recommendation with Knowledge Graph
Weizhi Ma, Min Zhang, Yue Cao +6
Explainability and effectiveness are two key aspects for building recommender systems. Prior efforts mostly focus on incorporating side information to achieve better recommendation…