Ke, Guolin

23 publications

ICML 2025 Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling Shuqi Lu, Xiaohong Ji, Bohang Zhang, Lin Yao, Siyuan Liu, Zhifeng Gao, Linfeng Zhang, Guolin Ke

ICCV 2025 MolParser: End-to-End Visual Recognition of Molecule Structures in the Wild Xi Fang, Jiankun Wang, Xiaochen Cai, Shangqian Chen, Shuwen Yang, Haoyi Tao, Nan Wang, Lin Yao, Linfeng Zhang, Guolin Ke

ICLR 2025 SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai

TMLR 2024 3D Molecular Generation via Virtual Dynamics Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke

NeurIPS 2024 Exploring Molecular Pretraining Model at Scale Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E

NeurIPS 2024 S-MolSearch: 3D Semi-Supervised Contrastive Learning for Bioactive Molecule Search Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei, Zhifeng Gao

NeurIPSW 2024 SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai

NeurIPSW 2023 Amalga: Designable Protein Backbone Generation with Folding and Inverse Folding Guidance Shugao Chen, Ziyao Li, Xiangxiang Zeng, Guolin Ke

ICLRW 2023 Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation? Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke

ICLRW 2023 Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking? Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke

NeurIPSW 2023 UMD-Fit: Generating Realistic Ligand Conformations for Distance-Based Deep Docking Models Eric Alcaide, Ziyao Li, Hang Zheng, Zhifeng Gao, Guolin Ke

ICLRW 2023 Uni-Fold MuSSe: De Novo Protein Complex Prediction with Protein Language Models Jinhua Zhu, Zhenyu He, Ziyao Li, Guolin Ke, Linfeng Zhang

ICLR 2023 Uni-Mol: A Universal 3D Molecular Representation Learning Framework Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke

NeurIPS 2022 Quantized Training of Gradient Boosting Decision Trees Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

NeurIPS 2021 Do Transformers Really Perform Badly for Graph Representation? Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

ICML 2021 How Could Neural Networks Understand Programs? Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

ICLR 2021 Rethinking Positional Encoding in Language Pre-Training Guolin Ke, Di He, Tie-Yan Liu

NeurIPS 2021 Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu

ICLR 2021 Taking Notes on the Fly Helps Language Pre-Training Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

ECCV 2020 Invertible Image Rescaling Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu

AAAI 2020 Light Multi-Segment Activation for Model Compression Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu

NeurIPS 2017 LightGBM: A Highly Efficient Gradient Boosting Decision Tree Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu

NeurIPS 2016 A Communication-Efficient Parallel Algorithm for Decision Tree Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Tie-Yan Liu