Meng, Qi

23 publications

IJCAI 2025 Generate or Re-Weight? a Mutual-Guidance Method for Class-Imbalanced Graphs Zhongying Zhao, Gen Liu, Qi Meng, Chao Li, Qingtian Zeng

ICLR 2025 HR-Extreme: A High-Resolution Dataset for Extreme Weather Forecasting Nian Ran, Peng Xiao, Yue Wang, Wesley Shi, Jianxin Lin, Qi Meng, Richard Allmendinger

ICLR 2023 $\mathcal{O}$-GNN: Incorporating Ring Priors into Molecular Modeling Jinhua Zhu, Kehan Wu, Bohan Wang, Yingce Xia, Shufang Xie, Qi Meng, Lijun Wu, Tao Qin, Wengang Zhou, Houqiang Li, Tie-Yan Liu

AAAI 2023 Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations Shiqi Gong, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhiming Ma, Hao Ni, Tie-Yan Liu

ICML 2023 NeuralStagger: Accelerating Physics-Constrained Neural PDE Solver with Spatial-Temporal Decomposition Xinquan Huang, Wenlei Shi, Qi Meng, Yue Wang, Xiaotian Gao, Jia Zhang, Tie-Yan Liu

NeurIPS 2022 Does Momentum Change the Implicit Regularization on Separable Data? Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu

ICLR 2022 PriorGrad: Improving Conditional Denoising Diffusion Models with Data-Dependent Adaptive Prior Sang-gil Lee, Heeseung Kim, Chaehun Shin, Xu Tan, Chang Liu, Qi Meng, Tao Qin, Wei Chen, Sungroh Yoon, Tie-Yan Liu

ICML 2022 SE(3) Equivariant Graph Neural Networks with Complete Local Frames Weitao Du, He Zhang, Yuanqi Du, Qi Meng, Wei Chen, Nanning Zheng, Bin Shao, Tie-Yan Liu

NeurIPS 2021 Optimizing Information-Theoretical Generalization Bound via Anisotropic Noise of SGLD Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu

UAI 2021 Path-BN: Towards Effective Batch Normalization in the Path Space for ReLU Networks Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu

NeurIPS 2021 R-Drop: Regularized Dropout for Neural Networks Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu

ICML 2021 The Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks Bohan Wang, Qi Meng, Wei Chen, Tie-Yan Liu

IJCAI 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations Xufang Luo, Qi Meng, Di He, Wei Chen, Yunhong Wang

IJCAI 2020 Reinforcement Learning with Dynamic Boltzmann SoftMax Updates Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang

AAAI 2019 Capacity Control of ReLU Neural Networks by Basis-Path Norm Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu

ICLR 2019 G-SGD: Optimizing ReLU Neural Networks in Its Positively Scale-Invariant Space Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu

IJCAI 2018 Differential Equations for Modeling Asynchronous Algorithms Li He, Qi Meng, Wei Chen, Zhiming Ma, Tie-Yan Liu

ICML 2017 Asynchronous Stochastic Gradient Descent with Delay Compensation Shuxin Zheng, Qi Meng, Taifeng Wang, Wei Chen, Nenghai Yu, Zhi-Ming Ma, Tie-Yan Liu

AAAI 2017 Asynchronous Stochastic Proximal Optimization Algorithms with Variance Reduction Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu

AAAI 2017 Generalization Error Bounds for Optimization Algorithms via Stability Qi Meng, Yue Wang, Wei Chen, Taifeng Wang, Zhiming Ma, 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

IJCAI 2016 Asynchronous Accelerated Stochastic Gradient Descent Qi Meng, Wei Chen, Jingcheng Yu, Taifeng Wang, Zhiming Ma, Tie-Yan Liu