Zhi-Ming Ma - RankMe

87 papers A* 28B 1Journal 56Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data. CoRR Peiyan Hu, Haodong Feng, Hongyuan Liu, Tongtong Yan, Wenhao Deng, Tianrun Gao, Rong Zheng, Haoren Zheng, Chenglei Yu, Chuanrui Wang, Kaiwen Li, Zhi-Ming Ma, Dezhi Zhou, Xingcai Lu, Dixia Fan, Tailin Wu
2026	J	`jnl`	Theoretical Analyses of Detectors for Additive Noise Channels with Mean-Variance Uncertainty under Nonlinear Expectation Theory. CoRR Wenxuan Lang, Guiying Yan, Zhi-Ming Ma
2026	J	`jnl`	UniFluids: Unified Neural Operator Learning with Conditional Flow-matching. CoRR Haosen Li, Qi Meng, Jiahao Li, Rui Zhang, Ruihua Song, Liang Ma, Zhi-Ming Ma
2025	J	`jnl`	A criterion for selecting the appropriate one from the trained models for model-based offline policy evaluation. CAAI Trans. Intell. Technol. Chongchong Li, Yue Wang, Zhi-Ming Ma, Yuting Liu
2025	J	`jnl`	Advantage Weighted Matching: Aligning RL with Pretraining in Diffusion Models. CoRR Shuchen Xue, Chongjian Ge, Shilong Zhang, Yichen Li, Zhi-Ming Ma
2025	J	`jnl`	Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture. CoRR Shuchen Xue, Tianyu Xie, Tianyang Hu, Zijin Feng, Jiacheng Sun, Kenji Kawaguchi, Zhenguo Li, Zhi-Ming Ma
2025	J	`jnl`	Erlang Model for Multi-Type Data Flow. IEEE Commun. Lett. Liuquan Yao, Pei Yang, Zhichao Liu, Wenyan Li, Jianghua Liu, Zhi-Ming Ma
2025	A*	`conf`	From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control. ICML Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2025	J	`jnl`	From Uncertain to Safe: Conformal Fine-Tuning of Diffusion Models for Safe PDE Control. CoRR Peiyan Hu, Xiaowei Qian, Wenhao Deng, Rui Wang, Haodong Feng, Ruiqi Feng, Tao Zhang, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2025	J	`jnl`	Graffe: Graph Representation Learning via Diffusion Probabilistic Models. CoRR Dingshuo Chen, Shuchen Xue, Liuji Chen, Yingheng Wang, Qiang Liu, Shu Wu, Zhi-Ming Ma, Liang Wang
2025	J	`jnl`	Improved Diffusion-based Generative Model with Better Adversarial Robustness. CoRR Zekun Wang, Mingyang Yi, Shuchen Xue, Zhenguo Li, Ming Liu, Bing Qin, Zhi-Ming Ma
2025	J	`jnl`	Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation. IEEE Trans. Pattern Anal. Mach. Intell. Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu
2025	J	`jnl`	OmniFluids: Unified Physics Pre-trained Modeling of Fluid Dynamics. CoRR Rui Zhang, Qi Meng, Han Wan, Yang Liu, Zhi-Ming Ma, Hao Sun
2025	J	`jnl`	On the Design of One-step Diffusion via Shortcutting Flow Paths. CoRR Haitao Lin, Peiyan Hu, Minsi Ren, Zhifeng Gao, Zhi-Ming Ma, Guolin Ke, Tailin Wu, Stan Z. Li
2025	J	`jnl`	Riemannian Neural Geodesic Interpolant. CoRR Jiawen Wu, Bingguang Chen, Yuyi Zhou, Qi Meng, Rongchan Zhu, Zhi-Ming Ma
2025	J	`jnl`	Semantic Rate-Distortion Theory with Applications. CoRR Yi-Qun Zhao, Zhi-Ming Ma, Geoffrey Ye Li, Shuai Yuan, Tong Ye, Chuan Zhou
2025	J	`jnl`	Straight-Line Diffusion Model for Efficient 3D Molecular Generation. CoRR Yuyan Ni, Shikun Feng, Haohan Chi, Bowen Zheng, Huan-ang Gao, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2025	A*	`conf`	UniGEM: A Unified Approach to Generation and Property Prediction for Molecules. ICLR Shikun Feng, Yuyan Ni, Yan Lu, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2025	A*	`conf`	Wavelet Diffusion Neural Operator. ICLR Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	J	`jnl`	A Generative Approach to Control Complex Physical Systems. CoRR Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	A*	`conf`	Better Neural PDE Solvers Through Data-Free Mesh Movers. ICLR Peiyan Hu, Yue Wang, Zhi-Ming Ma
2024	A*	`conf`	DiffPhyCon: A Generative Approach to Control Complex Physical Systems. NeurIPS Long Wei, Peiyan Hu, Ruiqi Feng, Haodong Feng, Yixuan Du, Tao Zhang, Rui Wang, Yue Wang, Zhi-Ming Ma, Tailin Wu
2024	J	`jnl`	Entropic Conditional Central Limit Theorem and Hadamard Compression. CoRR Zhi-Ming Ma, Liuquan Yao, Shuai Yuan, Huazi Zhang
2024	J	`jnl`	Erlang Model for Multiple Data Streams (Full Version). CoRR Liuquan Yao, Pei Yang, Zhichao Liu, Wenyan Li, Jianghua Liu, Zhi-Ming Ma
2024	A*	`conf`	Neural Jump-Diffusion Temporal Point Processes. ICML Shuai Zhang, Chuan Zhou, Yang Aron Liu, Peng Zhang, Xixun Lin, Zhi-Ming Ma
2024	J	`jnl`	Neural networks taking probability distributions as input: A framework for analyzing exchangeable networks. Neurocomputing Chongchong Li, Yuting Liu, Zhi-Ming Ma
2024	B	`conf`	New Partial Orders of Polar Codes for BMSC. ISIT Liuquan Yao, Zhichao Liu, Yuan Li, Huazi Zhang, Jun Wang, Guiying Yan, Zhi-Ming Ma
2024	J	`jnl`	On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. CoRR Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen
2024	J	`jnl`	Pre-training with Fractional Denoising to Enhance Molecular Property Prediction. CoRR Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan
2024	J	`jnl`	Pre-training with fractional denoising to enhance molecular property prediction. Nat. Mac. Intell. Yuyan Ni, Shikun Feng, Xin Hong, Yuancheng Sun, Wei-Ying Ma, Zhi-Ming Ma, Qiwei Ye, Yanyan Lan
2024	A*	`conf`	Provable Adaptivity of Adam under Non-uniform Smoothness. KDD Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Tie-Yan Liu, Zhi-Quan Luo, Wei Chen
2024	J	`jnl`	Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey. CoRR Haixin Wang, Yadi Cao, Zijie Huang, Yuxuan Liu, Peiyan Hu, Xiao Luo, Zezheng Song, Wanjia Zhao, Jilin Liu, Jinan Sun, Shikun Zhang, Long Wei, Yue Wang, Tailin Wu, Zhi-Ming Ma, Yizhou Sun
2024	A*	`conf`	Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion. ICML Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2024	J	`jnl`	Rethinking Specificity in SBDD: Leveraging Delta Score and Energy-Guided Diffusion. CoRR Bowen Gao, Minsi Ren, Yuyan Ni, Yanwen Huang, Bo Qiang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2024	A*	`conf`	Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment. ICLR Bowen Gao, Yinjun Jia, Yuanle Mo, Yuyan Ni, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2024	A*	`conf`	Sliced Denoising: A Physics-Informed Molecular Pre-Training Method. ICLR Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2024	A*	`conf`	The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. ICML Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
2024	J	`jnl`	The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
2024	A*	`conf`	UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning. ICML Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2024	J	`jnl`	UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning. CoRR Shikun Feng, Yuyan Ni, Minghao Li, Yanwen Huang, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2024	J	`jnl`	UniGEM: A Unified Approach to Generation and Property Prediction for Molecules. CoRR Shikun Feng, Yuyan Ni, Yan Lu, Zhi-Ming Ma, Wei-Ying Ma, Yanyan Lan
2024	J	`jnl`	Wavelet Diffusion Neural Operator. CoRR Peiyan Hu, Rui Wang, Xiang Zheng, Tao Zhang, Haodong Feng, Ruiqi Feng, Long Wei, Yue Wang, Zhi-Ming Ma, Tailin Wu
2023	A*	`conf`	A Group Symmetric Stochastic Differential Equation Model for Molecule Multi-modal Pretraining. ICML Shengchao Liu, Weitao Du, Zhi-Ming Ma, Hongyu Guo, Jian Tang
2023	A*	`conf`	A new perspective on building efficient and expressive 3D equivariant graph neural networks. NeurIPS Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla P. Gomes, Zhi-Ming Ma
2023	J	`jnl`	A new perspective on building efficient and expressive 3D equivariant graph neural networks. CoRR Weitao Du, Yuanqi Du, Limei Wang, Dieqiao Feng, Guifeng Wang, Shuiwang Ji, Carla Gomes, Zhi-Ming Ma
2023	J	`jnl`	Better Neural PDE Solvers Through Data-Free Mesh Movers. CoRR Peiyan Hu, Yue Wang, Zhi-Ming Ma
2023	A*	`conf`	Breaking Correlation Shift via Conditional Invariant Regularizer. ICLR Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
2023	J	`jnl`	Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen
2023	J	`jnl`	Deciphering and integrating invariants for neural operator learning with various physical mechanisms. CoRR Rui Zhang, Qi Meng, Zhi-Ming Ma
2023	A*	`conf`	Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. ICML Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma
2023	A*	`conf`	Fractional Denoising for 3D Molecular Pre-training. ICML Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma
2023	J	`jnl`	Fractional Denoising for 3D Molecular Pre-training. CoRR Shikun Feng, Yuyan Ni, Yanyan Lan, Zhi-Ming Ma, Wei-Ying Ma
2023	—	`conf`	How to Select the Appropriate One from the Trained Models for Model-Based OPE. CICAI (2) Chongchong Li, Yue Wang, Zhi-Ming Ma, Yuting Liu
2023	A*	`conf`	Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion. NeurIPS Weitao Du, Jiujiu Chen, Xuecang Zhang, Zhi-Ming Ma, Shengchao Liu
2023	J	`jnl`	Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation. CoRR Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu
2023	J	`jnl`	Power-law Dynamic arising from machine learning. CoRR Wei Chen, Weitao Du, Zhi-Ming Ma, Qi Meng
2023	A*	`conf`	SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models. NeurIPS Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
2023	J	`jnl`	SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models. CoRR Shuchen Xue, Mingyang Yi, Weijian Luo, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
2023	J	`jnl`	Sliced Denoising: A Physics-Informed Molecular Pre-Training Method. CoRR Yuyan Ni, Shikun Feng, Wei-Ying Ma, Zhi-Ming Ma, Yanyan Lan
2023	A*	`conf`	Symmetry-Informed Geometric Representation for Molecules, Proteins, and Crystalline Materials. NeurIPS Shengchao Liu, Weitao Du, Yanjing Li, Zhuoxinran Li, Zhiling Zheng, Chenru Duan, Zhi-Ming Ma, Omar Yaghi, Animashree Anandkumar, Christian Borgs, Jennifer T. Chayes, Hongyu Guo, Jian Tang
2022	A*	`conf`	Characterization of Excess Risk for Locally Strongly Convex Population Risk. NeurIPS Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
2022	J	`jnl`	Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations. CoRR Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu
2022	A*	`conf`	Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2022	A*	`conf`	Gradient Information Matters in Policy Optimization by Back-propagating through Model. ICLR Chongchong Li, Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu
2022	J	`jnl`	Improved OOD Generalization via Conditional Invariant Regularizer. CoRR Mingyang Yi, Ruoyu Wang, Jiacheng Sun, Zhenguo Li, Zhi-Ming Ma
2022	J	`jnl`	Neural Operator with Regularity Structure for Modeling Dynamics Driven by SPDEs. CoRR Peiyan Hu, Qi Meng, Bingguang Chen, Shiqi Gong, Yue Wang, Wei Chen, Rongchan Zhu, Zhi-Ming Ma, Tie-Yan Liu
2022	J	`jnl`	Provable Adaptivity in Adam. CoRR Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen
2022	A*	`conf`	When Does Group Invariant Learning Survive Spurious Correlations? NeurIPS Yimeng Chen, Ruibin Xiong, Zhi-Ming Ma, Yanyan Lan
2021	J	`jnl`	BN-invariant sharpness regularizes the training model to better generalization. CoRR Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2021	J	`jnl`	Improved OOD Generalization via Adversarial Training and Pre-training. CoRR Mingyang Yi, Lu Hou, Jiacheng Sun, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	J	`jnl`	Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics. CoRR Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2021	J	`jnl`	Momentum Doesn't Change the Implicit Bias. CoRR Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma
2021	A*	`conf`	Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. ICLR Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	J	`jnl`	Reweighting Augmented Samples by Minimizing the Maximal Expected Loss. CoRR Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
2021	J	`jnl`	Towards Accelerating Training of Batch Normalization: A Manifold Perspective. CoRR Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma
2021	A*	`conf`	Uncertainty Calibration for Ensemble-Based Debiasing Methods. NeurIPS Ruibin Xiong, Yimeng Chen, Liang Pang, Xueqi Cheng, Zhi-Ming Ma, Yanyan Lan
2020	J	`jnl`	Dynamic of Stochastic Gradient Descent with State-Dependent Noise. CoRR Qi Meng, Shiqi Gong, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2020	J	`jnl`	Non-Asymptotic Analysis of Excess Risk via Empirical Risk Landscape. CoRR Mingyang Yi, Ruoyu Wang, Zhi-Ming Ma
2020	J	`jnl`	Target transfer Q-learning and its convergence analysis. Neurocomputing Yue Wang, Yuting Liu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2020	J	`jnl`	The scale-invariant space for attention layer in neural network. Neurocomputing Yue Wang, Yuting Liu, Zhi-Ming Ma
2019	A*	`conf`	BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2019	J	`jnl`	Convergence analysis of distributed stochastic gradient descent with shuffling. Neurocomputing Qi Meng, Wei Chen, Yue Wang, Zhi-Ming Ma, Tie-Yan Liu
2019	—	`conf`	G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
2019	A*	`conf`	Off-policy Learning for Multiple Loggers. KDD Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin
2019	J	`jnl`	Off-policy Learning for Multiple Loggers. CoRR Li He, Long Xia, Wei Zeng, Zhi-Ming Ma, Yihong Zhao, Dawei Yin
2019	J	`jnl`	Positively Scale-Invariant Flatness of ReLU Neural Networks. CoRR Mingyang Yi, Qi Meng, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
2018	J	`jnl`	Finite Sample Analysis of the GTD Policy Evaluation Algorithms in Markov Setting. CoRR Yue Wang, Wei Chen, Yuting Liu, Zhi-Ming Ma, Tie-Yan Liu