Publication Exploring deep learning for air pollutant emission estimation Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, Tie-Yan Liu Geoscientific Model Development | July 2021, Vol 14(7): pp. 4641-4654
Publication Complementing sequence-derived features with structural information extracted from fragment libraries for protein structure prediction Siyuan Liu, Qijiang Xu, Tong Wang, Bin Shao, Jian Yin, Tie-Yan Liu BMC Bioinformatics | June 2021, Vol 22(1): pp. 351-351
Publication Machine-learning Nonconservative Dynamics for New Physics Detection Ziming Liu, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu Physical Review E | June 2021
Publication SAMF: a Self-adaptive Protein Modeling Framework Wenze Ding, Qijiang Xu, Siyuan Liu, Tong Wang, Bin Shao, Haipeng Gong, Tie-Yan Liu Bioinformatics | May 2021 Project
Publication CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction Fusong Ju, Jianwei Zhu, Bin Shao, Lupeng Kong, Tie-Yan Liu, Wei-Mou Zheng, Dongbo Bu Nature Communications | May 2021, Vol 12(1): pp. 2535-2535 Project
Publication Deep learning for prediction of the air quality response to emission changes Jia Xing, Shuxin Zheng, Dian Ding, James T Kelly, Shuxiao Wang, Siwei Li, Tao Qin, Mingyuan Ma, Zhaoxin Dong, Carey J. Jang, Yun Zhu, Haotian Zheng, Lu Ren, Tie-Yan Liu, Jiming Hao Environmental Science & Technology | June 2020, Vol 54(14): pp. 8589-8600
Publication Constrained Graph Variational Autoencoders for Molecule Design Qi Liu, Miltos Allamanis, Marc Brockschmidt, Alexander Gaunt NIPS 2018 | December 2018 Project Project
Publication Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties. Tian Xie, Jeffrey Grossman Physical Review Letters | April 2018, Vol 120(14): pp. 145301
Research
Research