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2020 – today
- 2024
[j2]Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke:
3D Molecular Generation via Virtual Dynamics. Trans. Mach. Learn. Res. 2024 (2024)- [i34]Qingsi Lai, Lin Yao, Zhifeng Gao, Siyuan Liu, Hongshuai Wang, Shuqi Lu, Di He, Liwei Wang, Cheng Wang, Guolin Ke:
End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction. CoRR abs/2401.03862 (2024) - [i33]Hengxing Cai, Xiaochen Cai, Junhan Chang, Sihang Li, Lin Yao, Changxin Wang, Zhifeng Gao, Hongshuai Wang, Yongge Li, Mujie Lin, Shuwen Yang, Jiankun Wang, Yuqi Yin, Yaqi Li, Linfeng Zhang, Guolin Ke:
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis. CoRR abs/2403.01976 (2024) - [i32]Hengxing Cai, Xiaochen Cai, Shuwen Yang, Jiankun Wang, Lin Yao, Zhifeng Gao, Junhan Chang, Sihang Li, Mingjun Xu, Changxin Wang, Hongshuai Wang, Yongge Li, Mujie Lin, Yaqi Li, Yuqi Yin, Linfeng Zhang, Guolin Ke:
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer. CoRR abs/2403.10301 (2024) - [i31]Eric Alcaide, Zhifeng Gao, Guolin Ke, Yaqi Li, Linfeng Zhang, Hang Zheng, Gengmo Zhou:
Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction. CoRR abs/2405.11769 (2024) - [i30]Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E:
Uni-Mol2: Exploring Molecular Pretraining Model at Scale. CoRR abs/2406.14969 (2024) - [i29]Sihang Li, Jin Huang, Jiaxi Zhuang, Yaorui Shi, Xiaochen Cai, Mingjun Xu, Xiang Wang, Linfeng Zhang, Guolin Ke, Hengxing Cai:
SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding. CoRR abs/2408.15545 (2024) - [i28]Shang Xiang, Lin Yao, Zhen Wang, Qifan Yu, Wentan Liu, Wentao Guo, Guolin Ke:
A high-accuracy multi-model mixing retrosynthetic method. CoRR abs/2409.04335 (2024) - [i27]Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei, Zhifeng Gao:
S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search. CoRR abs/2409.07462 (2024) - 2023
- [c14]Gengmo Zhou, Zhifeng Gao, Qiankun Ding, Hang Zheng
, Hongteng Xu, Zhewei Wei, Linfeng Zhang, Guolin Ke:
Uni-Mol: A Universal 3D Molecular Representation Learning Framework. ICLR 2023 - [i26]Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke:
3D Molecular Generation via Virtual Dynamics. CoRR abs/2302.05847 (2023) - [i25]Lin Yao, Ruihan Xu, Zhifeng Gao, Guolin Ke, Yuhang Wang:
Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM. CoRR abs/2302.06091 (2023) - [i24]Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke:
Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation? CoRR abs/2302.07061 (2023) - [i23]Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke:
Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking? CoRR abs/2302.07134 (2023) - [i22]Shuqi Lu, Zhifeng Gao, Di He, Linfeng Zhang, Guolin Ke:
Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+. CoRR abs/2303.16982 (2023) - [i21]Zhifeng Gao, Xiaohong Ji, Guojiang Zhao, Hongshuai Wang, Hang Zheng, Guolin Ke, Linfeng Zhang:
Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction. CoRR abs/2304.12239 (2023) - [i20]Lin Yao, Zhen Wang, Wentao Guo, Shang Xiang, Wentan Liu, Guolin Ke:
Node-Aligned Graph-to-Graph Generation for Retrosynthesis Prediction. CoRR abs/2309.15798 (2023) - 2022
- [c13]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. NeurIPS 2022 - [i19]Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu:
Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets. CoRR abs/2203.04810 (2022) - [i18]Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao:
METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals. CoRR abs/2204.06644 (2022) - [i17]Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu:
Quantized Training of Gradient Boosting Decision Trees. CoRR abs/2207.09682 (2022) - 2021
- [j1]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. IEEE Trans. Neural Networks Learn. Syst. 32(4): 1713-1722 (2021) - [c12]Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder. EMNLP (1) 2021: 2780-2791 - [c11]Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
Taking Notes on the Fly Helps Language Pre-Training. ICLR 2021 - [c10]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. ICLR 2021 - [c9]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? ICML 2021: 8476-8486 - [c8]Abhishek Das, Muhammed Shuaibi, Aini Palizhati, Siddharth Goyal, Aditya Grover, Adeesh Kolluru, Janice Lan, Ammar Rizvi, Anuroop Sriram, Brandon M. Wood, Devi Parikh, Zachary W. Ulissi, C. Lawrence Zitnick, Guolin Ke, Shuxin Zheng, Yu Shi, Di He, Tie-Yan Liu, Chengxuan Ying, Jiacheng You, Yihan He, Rostislav Grigoriev, Ruslan Lukin, Adel Yarullin, Max Faleev:
The Open Catalyst Challenge 2021: Competition Report. NeurIPS (Competition and Demos) 2021: 29-40 - [c7]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. NeurIPS 2021: 22795-22807 - [c6]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Badly for Graph Representation? NeurIPS 2021: 28877-28888 - [i16]Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu:
Revisiting Language Encoding in Learning Multilingual Representations. CoRR abs/2102.08357 (2021) - [i15]Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk:
Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder. CoRR abs/2102.09206 (2021) - [i14]Chengxuan Ying, Guolin Ke, Di He, Tie-Yan Liu:
LazyFormer: Self Attention with Lazy Update. CoRR abs/2102.12702 (2021) - [i13]Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio:
Transformers with Competitive Ensembles of Independent Mechanisms. CoRR abs/2103.00336 (2021) - [i12]Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
How could Neural Networks understand Programs? CoRR abs/2105.04297 (2021) - [i11]Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu:
Do Transformers Really Perform Bad for Graph Representation? CoRR abs/2106.05234 (2021) - [i10]Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He:
First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track. CoRR abs/2106.08279 (2021) - [i9]Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He:
Deep Subdomain Adaptation Network for Image Classification. CoRR abs/2106.09388 (2021) - [i8]Shengjie Luo, Shanda Li, Tianle Cai, Di He, Dinglan Peng, Shuxin Zheng, Guolin Ke, Liwei Wang, Tie-Yan Liu:
Stable, Fast and Accurate: Kernelized Attention with Relative Positional Encoding. CoRR abs/2106.12566 (2021) - 2020
- [c5]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-Segment Activation for Model Compression. AAAI 2020: 6542-6549 - [c4]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. ECCV (1) 2020: 126-144 - [i7]Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu:
Invertible Image Rescaling. CoRR abs/2005.05650 (2020) - [i6]Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu:
MC-BERT: Efficient Language Pre-Training via a Meta Controller. CoRR abs/2006.05744 (2020) - [i5]Guolin Ke, Di He, Tie-Yan Liu:
Rethinking Positional Encoding in Language Pre-training. CoRR abs/2006.15595 (2020) - [i4]Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu:
Taking Notes on the Fly Helps BERT Pre-training. CoRR abs/2008.01466 (2020)
2010 – 2019
- 2019
- [c3]Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu:
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks. KDD 2019: 384-394 - [i3]Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu:
Light Multi-segment Activation for Model Compression. CoRR abs/1907.06870 (2019) - [i2]Ziyu Liu, Guolin Ke, Jiang Bian, Tie-Yan Liu:
LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm. CoRR abs/1908.09362 (2019) - 2017
- [c2]Guolin Ke, Qi Meng, Thomas Finley, Taifeng Wang, Wei Chen, Weidong Ma, Qiwei Ye, Tie-Yan Liu:
LightGBM: A Highly Efficient Gradient Boosting Decision Tree. NIPS 2017: 3146-3154 - 2016
- [c1]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. NIPS 2016: 1271-1279 - [i1]Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu:
A Communication-Efficient Parallel Algorithm for Decision Tree. CoRR abs/1611.01276 (2016)
Coauthor Index
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last updated on 2024-11-15 19:35 CET by the dblp team
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