Generalization Error Bounds for Optimization Algorithms via Stability. - Qi Meng; Yue Wang 017; Wei Chen 034; Taifeng Wang; Zhiming Ma; Tie-Yan Liu (AAAI, 2017)

Finite sample analysis of the GTD Policy Evaluation Algorithms in Markov Setting. - Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (NIPS, 2017)

Target Transfer Q-Learning and Its Convergence Analysis. - Yue Wang 017; Qi Meng; Wei Chen 034; Yuting Liu 002; Zhiming Ma; Tie-Yan Liu (CoRR, 2018)

Convergence analysis of distributed stochastic gradient descent with shuffling. - Qi Meng; Wei Chen 034; Yue Wang 017; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2019)

Target transfer Q-learning and its convergence analysis. - Yue Wang 017; Yuting Liu 002; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (Neurocomputing, 2020)

The scale-invariant space for attention layer in neural network. - Yue Wang 017; Yuting Liu 002; Zhi-Ming Ma (Neurocomputing, 2020)

Gradient Information Matters in Policy Optimization by Back-propagating through Model. - Chongchong Li; Yue Wang 017; Wei Chen 034; Yuting Liu 002; Zhi-Ming Ma; Tie-Yan Liu (ICLR, 2022)

Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. - Peiyan Hu; Qi Meng; Bingguang Chen; Shiqi Gong; Yue Wang 017; Wei Chen 034; Rongchan Zhu; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2022)

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. - Rui Zhang 052; Peiyan Hu; Qi Meng; Yue Wang 017; Rongchan Zhu; Bingguang Chen; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2022)

Constructing the Basis Path Set by Eliminating the Path Dependency. - Juanping Zhu; Qi Meng; Wei Chen 034; Yue Wang 017; Zhiming Ma (J. Syst. Sci. Complex., 2022)

Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations. - Shiqi Gong; Peiyan Hu; Qi Meng; Yue Wang 017; Rongchan Zhu; Bingguang Chen; Zhiming Ma; Hao Ni; Tie-Yan Liu (AAAI, 2023)

How to Select the Appropriate One from the Trained Models for Model-Based OPE. - Chongchong Li; Yue Wang 017; Zhi-Ming Ma; Yuting Liu 002 (CICAI (2), 2023)

Making Better Decision by Directly Planning in Continuous Control. - Jinhua Zhu 001; Yue Wang 017; Lijun Wu 003; Tao Qin 001; Wengang Zhou 001; Tie-Yan Liu; Houqiang Li (ICLR, 2023)

NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition. - Xinquan Huang; Wenlei Shi; Qi Meng; Yue Wang 017; Xiaotian Gao; Jia Zhang 004; Tie-Yan Liu (ICML, 2023)

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (CoRR, 2023)

How to Control Hydrodynamic Force on Fluidic Pinball via Deep Reinforcement Learning. - Haodong Feng; Yue Wang 017; Hui Xiang; Zhiyang Jin; Dixia Fan (CoRR, 2023)

Incorporating NODE with pre-trained neural differential operator for learning dynamics. - Shiqi Gong; Qi Meng; Yue Wang 017; Lijun Wu 003; Wei Chen 034; Zhiming Ma; Tie-Yan Liu (Neurocomputing, 2023)

Better Neural PDE Solvers Through Data-Free Mesh Movers. - Peiyan Hu; Yue Wang 017; Zhi-Ming Ma (ICLR, 2024)

DiffPhyCon: A Generative Approach to Control Complex Physical Systems. - Long Wei; Peiyan Hu; Ruiqi Feng; Haodong Feng; Yixuan Du; Tao Zhang 033; Rui Wang 017; Yue Wang 017; Zhi-Ming Ma; Tailin Wu (NeurIPS, 2024)

Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey. - Qizhi Pei; Lijun Wu 003; Kaiyuan Gao; Jinhua Zhu 001; Yue Wang 017; Zun Wang; Tao Qin 001; Rui Yan 001 (CoRR, 2024)

A Generative Approach to Control Complex Physical Systems. - Long Wei; Peiyan Hu; Ruiqi Feng; Haodong Feng; Yixuan Du; Tao Zhang 033; Rui Wang 017; Yue Wang 017; Zhi-Ming Ma; Tailin Wu (CoRR, 2024)

Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey. - Haixin Wang 003; Yadi Cao; Zijie Huang 002; Yuxuan Liu; Peiyan Hu; Xiao Luo 001; Zezheng Song; Wanjia Zhao; Jilin Liu; Jinan Sun; Shikun Zhang; Long Wei; et al. (CoRR, 2024)

Multimodal Policies with Physics-informed Representations. - Haodong Feng; Peiyan Hu; Yue Wang 017; Dixia Fan (CoRR, 2024)

How to Re-enable PDE Loss for Physical Systems Modeling Under Partial Observation. - Haodong Feng; Yue Wang 017; Dixia Fan (AAAI, 2025)

Wavelet Diffusion Neural Operator. - Peiyan Hu; Rui Wang 017; Xiang Zheng; Tao Zhang 033; Haodong Feng; Ruiqi Feng; Long Wei; Yue Wang 017; Zhi-Ming Ma; Tailin Wu (ICLR, 2025)

A criterion for selecting the appropriate one from the trained models for model-based offline policy evaluation. - Chongchong Li; Yue Wang 017; Zhi-Ming Ma; Yuting Liu 002 (CAAI Trans. Intell. Technol., 2025)

Disentangling Length Bias In Preference Learning Via Response-Conditioned Modeling. - Jianfeng Cai 008; Jinhua Zhu 001; Ruopei Sun; Yue Wang 017; Li Li 040; Wengang Zhou 001; Houqiang Li (CoRR, 2025)

From Uncertain to Safe: Conformal Fine-Tuning of Diffusion Models for Safe PDE Control. - Peiyan Hu; Xiaowei Qian; Wenhao Deng 001; Rui Wang 017; Haodong Feng; Ruiqi Feng; Tao Zhang 033; Long Wei; Yue Wang 017; Zhi-Ming Ma; Tailin Wu (CoRR, 2025)

Reveal the Mystery of DPO: The Connection between DPO and RL Algorithms. - Xuerui Su; Yue Wang 017; Jinhua Zhu 001; Mingyang Yi; Feng Xu; Zhiming Ma; Yuting Liu 002 (CoRR, 2025)

NatureLM: Deciphering the Language of Nature for Scientific Discovery. - Yingce Xia; Peiran Jin; Shufang Xie 003; Liang He 010; Chuan Cao; Renqian Luo; Guoqing Liu; Yue Wang 017; Zequn Liu; Yuan-Jyue Chen; Zekun Guo; Yeqi Bai; et al. (CoRR, 2025)

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning. - Xuerui Su; Shufang Xie 003; Guoqing Liu; Yingce Xia; Renqian Luo; Peiran Jin; Zhiming Ma; Yue Wang 017; Zun Wang; Yuting Liu 002 (CoRR, 2025)

Model-Based Closed-Loop Control Algorithm for Stochastic Partial Differential Equation Control. - Peiyan Hu; Haodong Feng; Yue Wang 017; Zhiming Ma (CoRR, 2025)

DGRO: Enhancing LLM Reasoning via Exploration-Exploitation Control and Reward Variance Management. - Xuerui Su; Liya Guo; Yue Wang 017; Yi Zhu 010; Zhiming Ma; Zun Wang; Yuting Liu 002 (CoRR, 2025)

Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. - Rui Zhang 052; Qi Meng; Rongchan Zhu; Yue Wang 017; Wenlei Shi; Shihua Zhang; Zhi-Ming Ma; Tie-Yan Liu (IEEE Trans. Pattern Anal. Mach. Intell., 2025)