210 citations · 239 across the 3 of their papers we have counts for
4 papers
MARS: Markov Molecular Sampling for Multi-objective Drug Discovery
Yutong Xie, Chence Shi, Hao Zhou +4
Searching for novel molecules with desired chemical properties is crucial in drug discovery. Existing work focuses on developing neural models to generate either molecular sequence…
Non-autoregressive electron flow generation for reaction prediction
Hangrui Bi, Hengyi Wang, Chence Shi +1
Reaction prediction is a fundamental problem in computational chemistry. Existing approaches typically generate a chemical reaction by sampling tokens or graph edits sequentially,…
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence Shi, Minkai Xu, Zhaocheng Zhu +3
Molecular graph generation is a fundamental problem for drug discovery and has been attracting growing attention. The problem is challenging since it requires not only generating c…
AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks
Weiping Song, Chence Shi, Zhiping Xiao +4
Click-through rate (CTR) prediction, which aims to predict the probability of a user clicking on an ad or an item, is critical to many online applications such as online advertisin…