95 citations · 118 across the 6 of their papers we have counts for
6 papers
EBM-Fold: Fully-Differentiable Protein Folding Powered by Energy-based Models
Jiaxiang Wu, Shitong Luo, Tao Shen +3
Accurate protein structure prediction from amino-acid sequences is critical to better understanding the protein function. Recent advances in this area largely benefit from more pre…
tFold-TR: Combining Deep Learning Enhanced Hybrid Potential Energy for Template-Based Modeling Structure Refinement
Liangzhen Zheng, Haidong Lan, Tao Shen +4
Protein structure prediction has been a grand challenge for over 50 years, owing to its broad scientific and application interests. There are two primary types of modeling algorith…
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation
Jinyu Yang, Weizhi An, Sheng Wang +3
Unsupervised domain adaptation enables to alleviate the need for pixel-wise annotation in the semantic segmentation. One of the most common strategies is to translate images from t…
Re-balancing Variational Autoencoder Loss for Molecule Sequence Generation
Chaochao Yan, Sheng Wang, Jinyu Yang +2
Molecule generation is to design new molecules with specific chemical properties and further to optimize the desired chemical properties. Following previous work, we encode molecul…
Adaptive Graph Convolutional Neural Networks
Ruoyu Li, Sheng Wang, Feiyun Zhu +1
Graph Convolutional Neural Networks (Graph CNNs) are generalizations of classical CNNs to handle graph data such as molecular data, point could and social networks. Current filters…
Robust Contextual Bandit via the Capped- norm
Feiyun Zhu, Xinliang Zhu, Sheng Wang +2
This paper considers the actor-critic contextual bandit for the mobile health (mHealth) intervention. The state-of-the-art decision-making methods in mHealth generally assume that…