Guolin Ke

According to our database, Guolin Ke authored at least 41 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

3D Molecular Generation via Virtual Dynamics.

Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke

Trans. Mach. Learn. Res., 2024

S-MolSearch: 3D Semi-supervised Contrastive Learning for Bioactive Molecule Search.

Gengmo Zhou, Zhen Wang, Feng Yu, Guolin Ke, Zhewei Wei, Zhifeng Gao

CoRR, 2024

A high-accuracy multi-model mixing retrosynthetic method.

Shang Xiang, Lin Yao, Zhen Wang, Qifan Yu, Wentan Liu, Wentao Guo, Guolin Ke

CoRR, 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

CoRR, 2024

Uni-Mol2: Exploring Molecular Pretraining Model at Scale.

Xiaohong Ji, Zhen Wang, Zhifeng Gao, Hang Zheng, Linfeng Zhang, Guolin Ke, Weinan E

CoRR, 2024

Uni-Mol Docking V2: Towards Realistic and Accurate Binding Pose Prediction.

Eric Alcaide, Zhifeng Gao, Guolin Ke, Yaqi Li, Linfeng Zhang, Hang Zheng, Gengmo Zhou

CoRR, 2024

Uni-SMART: Universal Science Multimodal Analysis and Research Transformer.

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

CoRR, 2024

SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis.

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

CoRR, 2024

End-to-End Crystal Structure Prediction from Powder X-Ray Diffraction.

Qingsi Lai, Lin Yao, Zhifeng Gao, Siyuan Liu, Hongshuai Wang, Shuqi Lu, Di He, Liwei Wang, Cheng Wang, Guolin Ke

CoRR, 2024

2023

Node-Aligned Graph-to-Graph Generation for Retrosynthesis Prediction.

Lin Yao, Zhen Wang, Wentao Guo, Shang Xiang, Wentan Liu, Guolin Ke

CoRR, 2023

Uni-QSAR: an Auto-ML Tool for Molecular Property Prediction.

Zhifeng Gao, Xiaohong Ji, Guojiang Zhao, Hongshuai Wang, Hang Zheng, Guolin Ke, Linfeng Zhang

CoRR, 2023

Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+.

Shuqi Lu, Zhifeng Gao, Di He, Linfeng Zhang, Guolin Ke

CoRR, 2023

Do Deep Learning Models Really Outperform Traditional Approaches in Molecular Docking?

Yuejiang Yu, Shuqi Lu, Zhifeng Gao, Hang Zheng, Guolin Ke

CoRR, 2023

Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?

Gengmo Zhou, Zhifeng Gao, Zhewei Wei, Hang Zheng, Guolin Ke

CoRR, 2023

Boosted ab initio Cryo-EM 3D Reconstruction with ACE-EM.

Lin Yao, Ruihan Xu, Zhifeng Gao, Guolin Ke, Yuhang Wang

CoRR, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals.

Payal Bajaj, Chenyan Xiong, Guolin Ke, Xiaodong Liu, Di He, Saurabh Tiwary, Tie-Yan Liu, Paul Bennett, Xia Song, Jianfeng Gao

CoRR, 2022

Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets.

Yu Shi, Shuxin Zheng, Guolin Ke, Yifei Shen, Jiacheng You, Jiyan He, Shengjie Luo, Chang Liu, Di He, Tie-Yan Liu

CoRR, 2022

Quantized Training of Gradient Boosting Decision Trees.

Yu Shi, Guolin Ke, Zhuoming Chen, Shuxin Zheng, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Deep Subdomain Adaptation Network for Image Classification.

Yongchun Zhu, Fuzhen Zhuang, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He

IEEE Trans. Neural Networks Learn. Syst., 2021

First Place Solution of KDD Cup 2021 & OGB Large-Scale Challenge Graph Prediction Track.

Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He

CoRR, 2021

Do Transformers Really Perform Bad for Graph Representation?

Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu

CoRR, 2021

Transformers with Competitive Ensembles of Independent Mechanisms.

Alex Lamb, Di He, Anirudh Goyal, Guolin Ke, Chien-Feng Liao, Mirco Ravanelli, Yoshua Bengio

CoRR, 2021

LazyFormer: Self Attention with Lazy Update.

Chengxuan Ying, Guolin Ke, Di He, Tie-Yan Liu

CoRR, 2021

Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder.

Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk

CoRR, 2021

Revisiting Language Encoding in Learning Multilingual Representations.

Shengjie Luo, Kaiyuan Gao, Shuxin Zheng, Guolin Ke, Di He, Liwei Wang, Tie-Yan Liu

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Open Catalyst Challenge 2021: Competition Report.

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

Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

How could Neural Networks understand Programs?

Dinglan Peng, Shuxin Zheng, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

Proceedings of the 38th International Conference on Machine Learning, 2021

Rethinking Positional Encoding in Language Pre-training.

Guolin Ke, Di He, Tie-Yan Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

Taking Notes on the Fly Helps Language Pre-Training.

Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

Proceedings of the 9th International Conference on Learning Representations, 2021

Less is More: Pretrain a Strong Siamese Encoder for Dense Text Retrieval Using a Weak Decoder.

Shuqi Lu, Di He, Chenyan Xiong, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tie-Yan Liu, Arnold Overwijk

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

Taking Notes on the Fly Helps BERT Pre-training.

Qiyu Wu, Chen Xing, Yatao Li, Guolin Ke, Di He, Tie-Yan Liu

CoRR, 2020

MC-BERT: Efficient Language Pre-Training via a Meta Controller.

Zhenhui Xu, Linyuan Gong, Guolin Ke, Di He, Shuxin Zheng, Liwei Wang, Jiang Bian, Tie-Yan Liu

CoRR, 2020

Invertible Image Rescaling.

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

Proceedings of the Computer Vision - ECCV 2020, 2020

Light Multi-Segment Activation for Model Compression.

Zhenhui Xu, Guolin Ke, Jia Zhang, Jiang Bian, Tie-Yan Liu

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

LightMC: A Dynamic and Efficient Multiclass Decomposition Algorithm.

Ziyu Liu, Guolin Ke, Jiang Bian, Tie-Yan Liu

CoRR, 2019

DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks.

Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016

A Communication-Efficient Parallel Algorithm for Decision Tree.

Qi Meng, Guolin Ke, Taifeng Wang, Wei Chen, Qiwei Ye, Zhiming Ma, Tie-Yan Liu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016