Qianxiao Li - RankMe

115 papers A* 23B 1Journal 84Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Deep learning and the rate of approximation by flows. CoRR Jingpu Cheng, Qianxiao Li, Ting Lin, Zuowei Shen
2026	J	`jnl`	MSign: An Optimizer Preventing Training Instability in Large Language Models via Stable Rank Restoration. CoRR Lianhai Ren, Yucheng Ding, Xiao Liu, Qianxiao Li, Peng Cheng, Yeyun Gong
2026	J	`jnl`	Machine Unlearning under Retain-Forget Entanglement. CoRR Jingpu Cheng, Ping Liu, Qianxiao Li, Chi Zhang
2026	J	`jnl`	Terminally constrained flow-based generative models from an optimal control perspective. CoRR Weiguo Gao, Ming Li, Qianxiao Li
2025	J	`jnl`	A unified framework on the universal approximation of transformer-type architectures. CoRR Jingpu Cheng, Qianxiao Li, Ting Lin, Zuowei Shen
2025	J	`jnl`	AI4X Roadmap: Artificial Intelligence for the advancement of scientific pursuit and its future directions. CoRR Stephen G. Dale, Nikita Kazeev, Alastair J. A. Price, Victor Posligua, Stephan Roche, O. Anatole von Lilienfeld, Konstantin S. Novoselov, Xavier Bresson, Gianmarco Mengaldo, Xudong Chen, Terence J. O'Kane, Emily R. Lines, Matthew J. Allen, Amandine E. Debus, Clayton Miller, Jiayu Zhou, Hiroko H. Dodge, David Rousseau, Andrey Ustyuzhanin, Ziyun Yan, Mario Lanza, Fabio Sciarrino, Ryo Yoshida, Zhidong Leong, Teck Leong Tan, Qianxiao Li, Adil Kabylda, Igor Poltavsky, Alexandre Tkatchenko, Sherif Abdulkader Tawfik, Prathami Divakar Kamath, Théo Jaffrelot Inizan, Kristin A. Persson, Bryant Y. Li, Vir Karan, Chenru Duan, Haojun Jia, Qiyuan Zhao, Hiroyuki Hayashi, Atsuto Seko, Isao Tanaka, Omar M. Yaghi, Tim Gould, Bun Chan, Stefan Vuckovic, Tianbo Li, Min Lin, Zehcen Tang, Yang Li, Yong Xu, Amrita Joshi, Xiaonan Wang, Leonard W. T. Ng, Sergei V. Kalinin, Mahshid Ahmadi, Jiyizhe Zhang, Shuyuan Zhang, Alexei A. Lapkin, Ming Xiao, Zhe Wu, Kedar Hippalgaonkar, Limsoon Wong, Lorenzo Bastonero, Nicola Marzari, Dorye Luis Esteras Cordoba, Andrei Tomut, Alba Quinones Andrade, Jose-Hugo Garcia
2025	J	`jnl`	Allocation of Parameters in Transformers. CoRR Ruoxi Yu, Haotian Jiang, Jingpu Cheng, Penghao Yu, Qianxiao Li, Zhong Li
2025	A*	`conf`	Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models. ICLR Fusheng Liu, Qianxiao Li
2025	A*	`conf`	BP-Modified Local Loss for Efficient Training of Deep Neural Networks. ICLR Lianhai Ren, Qianxiao Li
2025	A*	`conf`	Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images. ICLR Aiqing Zhu, Yuting Pan, Qianxiao Li
2025	J	`jnl`	Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images. CoRR Aiqing Zhu, Yuting Pan, Qianxiao Li
2025	A*	`conf`	From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control. ICML Chi Zhang, Lianhai Ren, Jingpu Cheng, Qianxiao Li
2025	J	`jnl`	Identifiable learning of dissipative dynamics. CoRR Aiqing Zhu, Beatrice W. Soh, Grigorios A. Pavliotis, Qianxiao Li
2025	J	`jnl`	Interpolation, Approximation, and Controllability of Deep Neural Networks. SIAM J. Control. Optim. Jingpu Cheng, Qianxiao Li, Ting Lin, Zuowei Shen
2025	J	`jnl`	Learning Parametric Koopman Decompositions for Prediction and Control. SIAM J. Appl. Dyn. Syst. Yue Guo, Milan Korda, Ioannis G. Kevrekidis, Qianxiao Li
2025	J	`jnl`	Learning task-specific predictive models for scientific computing. CoRR Jianyuan Yin, Qianxiao Li
2025	J	`jnl`	Mitigating Distribution Shift in Machine Learning-Augmented Hybrid Simulation. SIAM J. Sci. Comput. Jiaxi Zhao, Qianxiao Li
2025	J	`jnl`	Numerical Investigation of Sequence Modeling Theory using Controllable Memory Functions. CoRR Haotian Jiang, Zeyu Bao, Shida Wang, Qianxiao Li
2025	J	`jnl`	On the Universal Approximation Property of Deep Fully Convolutional Neural Networks. SIAM J. Math. Anal. Qianxiao Li, Ting Lin, Zuowei Shen
2025	J	`jnl`	Scalable learning of macroscopic stochastic dynamics. CoRR Mengyi Chen, Pengru Huang, Kostya S. Novoselov, Qianxiao Li
2025	J	`jnl`	The Effect of Attention Head Count on Transformer Approximation. CoRR Penghao Yu, Haotian Jiang, Zeyu Bao, Ruoxi Yu, Qianxiao Li
2025	J	`jnl`	The Effect of Depth on the Expressivity of Deep Linear State-Space Models. CoRR Zeyu Bao, Penghao Yu, Haotian Jiang, Qianxiao Li
2024	J	`jnl`	A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. SIAM J. Sci. Comput. Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis
2024	A*	`conf`	Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving. ICML Sohei Arisaka, Qianxiao Li
2024	J	`jnl`	Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving. CoRR Sohei Arisaka, Qianxiao Li
2024	—	`conf`	An Optimal Control View of LoRA and Binary Controller Design for Vision Transformers. ECCV (53) Chi Zhang, Jingpu Cheng, Qianxiao Li
2024	A*	`conf`	Approximation Rate of the Transformer Architecture for Sequence Modeling. NeurIPS Haotian Jiang, Qianxiao Li
2024	J	`jnl`	Autocorrelation Matters: Understanding the Role of Initialization Schemes for State Space Models. CoRR Fusheng Liu, Qianxiao Li
2024	J	`jnl`	Constructing custom thermodynamics using deep learning. Nat. Comput. Sci. Xiaoli Chen, Beatrice W. Soh, Zi-En Ooi, Eléonore Vissol-Gaudin, Haijun Yu, Kostya S. Novoselov, Kedar Hippalgaonkar, Qianxiao Li
2024	J	`jnl`	Deep Neural Network Approximation of Invariant Functions through Dynamical Systems. J. Mach. Learn. Res. Qianxiao Li, Ting Lin, Zuowei Shen
2024	J	`jnl`	DynGMA: A robust approach for learning stochastic differential equations from data. J. Comput. Phys. Aiqing Zhu, Qianxiao Li
2024	J	`jnl`	DynGMA: a robust approach for learning stochastic differential equations from data. CoRR Aiqing Zhu, Qianxiao Li
2024	A*	`conf`	From Generalization Analysis to Optimization Designs for State Space Models. ICML Fusheng Liu, Qianxiao Li
2024	J	`jnl`	From Generalization Analysis to Optimization Designs for State Space Models. CoRR Fusheng Liu, Qianxiao Li
2024	A*	`conf`	Inverse Approximation Theory for Nonlinear Recurrent Neural Networks. ICLR Shida Wang, Zhong Li, Qianxiao Li
2024	A*	`conf`	Learning Macroscopic Dynamics from Partial Microscopic Observations. NeurIPS Mengyi Chen, Qianxiao Li
2024	J	`jnl`	Learning Macroscopic Dynamics from Partial Microscopic Observations. CoRR Mengyi Chen, Qianxiao Li
2024	J	`jnl`	Mitigating distribution shift in machine learning-augmented hybrid simulation. CoRR Jiaxi Zhao, Qianxiao Li
2024	J	`jnl`	PID Control-Based Self-Healing to Improve the Robustness of Large Language Models. CoRR Zhuotong Chen, Zihu Wang, Yifan Yang, Qianxiao Li, Zheng Zhang
2024	J	`jnl`	PID Control-Based Self-Healing to Improve the Robustness of Large Language Models. Trans. Mach. Learn. Res. Zhuotong Chen, Zihu Wang, Yifan Yang, Qianxiao Li, Zheng Zhang
2024	A*	`conf`	Parameter-Efficient Fine-Tuning with Controls. ICML Chi Zhang, Jingpu Cheng, Yanyu Xu, Qianxiao Li
2024	A*	`conf`	StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization. ICML Shida Wang, Qianxiao Li
2024	J	`jnl`	Unifying back-propagation and forward-forward algorithms through model predictive control. CoRR Lianhai Ren, Qianxiao Li
2023	J	`jnl`	A Brief Survey on the Approximation Theory for Sequence Modelling. CoRR Haotian Jiang, Qianxiao Li, Zhong Li, Shida Wang
2023	J	`jnl`	An Annealing Mechanism for Adversarial Training Acceleration. IEEE Trans. Neural Networks Learn. Syst. Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2023	J	`jnl`	Approximation theory of transformer networks for sequence modeling. CoRR Haotian Jiang, Qianxiao Li
2023	J	`jnl`	Asymptotically Fair Participation in Machine Learning Models: an Optimal Control Perspective. CoRR Zhuotong Chen, Qianxiao Li, Zheng Zhang
2023	J	`jnl`	Computing high-dimensional invariant distributions from noisy data. J. Comput. Phys. Bo Lin, Qianxiao Li, Weiqing Ren
2023	J	`jnl`	Constructing Custom Thermodynamics Using Deep Learning. CoRR Xiaoli Chen, Beatrice W. Soh, Zi-En Ooi, Eléonore Vissol-Gaudin, Haijun Yu, Kostya S. Novoselov, Kedar Hippalgaonkar, Qianxiao Li
2023	J	`jnl`	Forward and Inverse Approximation Theory for Linear Temporal Convolutional Networks. CoRR Haotian Jiang, Qianxiao Li
2023	J	`jnl`	Interpolation, Approximation and Controllability of Deep Neural Networks. CoRR Jingpu Cheng, Qianxiao Li, Ting Lin, Zuowei Shen
2023	J	`jnl`	Inverse Approximation Theory for Nonlinear Recurrent Neural Networks. CoRR Shida Wang, Zhong Li, Qianxiao Li
2023	J	`jnl`	On stability and regularization for data-driven solution of parabolic inverse source problems. J. Comput. Phys. Mengmeng Zhang, Qianxiao Li, Jijun Liu
2023	A*	`conf`	Principled Acceleration of Iterative Numerical Methods Using Machine Learning. ICML Sohei Arisaka, Qianxiao Li
2023	J	`jnl`	StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization. CoRR Shida Wang, Qianxiao Li
2022	J	`jnl`	A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms. CoRR Danimir T. Doncevic, Alexander Mitsos, Yue Guo, Qianxiao Li, Felix Dietrich, Manuel Dahmen, Ioannis G. Kevrekidis
2022	J	`jnl`	Accelerating numerical methods by gradient-based meta-solving. CoRR Sohei Arisaka, Qianxiao Li
2022	—	`conf`	Adaptive sampling methods for learning dynamical systems. MSML Zichen Zhao, Qianxiao Li
2022	J	`jnl`	Approximation and Optimization Theory for Linear Continuous-Time Recurrent Neural Networks. J. Mach. Learn. Res. Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2022	J	`jnl`	Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning. J. Sci. Comput. Bo Lin, Qianxiao Li, Weiqing Ren
2022	J	`jnl`	Connecting Optimization and Generalization via Gradient Flow Path Length. CoRR Fusheng Liu, Haizhao Yang, Soufiane Hayou, Qianxiao Li
2022	J	`jnl`	Deep Neural Network Approximation of Invariant Functions through Dynamical Systems. CoRR Qianxiao Li, Ting Lin, Zuowei Shen
2022	J	`jnl`	Fast Bayesian Optimization of Needle-in-a-Haystack Problems using Zooming Memory-Based Initialization. CoRR Alexander E. Siemenn, Zekun Ren, Qianxiao Li, Tonio Buonassisi
2022	J	`jnl`	From Optimization Dynamics to Generalization Bounds via Łojasiewicz Gradient Inequality. Trans. Mach. Learn. Res. Fusheng Liu, Haizhao Yang, Soufiane Hayou, Qianxiao Li
2022	—	`ed.`	Mathematical and Scientific Machine Learning, 15-17 August 2022, Peking University, Beijing, China MSML Bin Dong, Qianxiao Li, Lei Wang, Zhi-Qin John Xu
2022	J	`jnl`	On the Universal Approximation Property of Deep Fully Convolutional Neural Networks. CoRR Ting Lin, Zuowei Shen, Qianxiao Li
2022	A*	`conf`	On the approximation properties of recurrent encoder-decoder architectures. ICLR Zhong Li, Haotian Jiang, Qianxiao Li
2022	J	`jnl`	Personalized Algorithm Generation: A Case Study in Learning ODE Integrators. SIAM J. Sci. Comput. Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li
2022	J	`jnl`	Self-Healing Robust Neural Networks via Closed-Loop Control. CoRR Zhuotong Chen, Qianxiao Li, Zheng Zhang
2022	J	`jnl`	Self-Healing Robust Neural Networks via Closed-Loop Control. J. Mach. Learn. Res. Zhuotong Chen, Qianxiao Li, Zheng Zhang
2022	J	`jnl`	Transfer Learning for Rapid Extraction of Thickness from Optical Spectra of Semiconductor Thin Films. CoRR Siyu Isaac Parker Tian, Zekun Ren, Selvaraj Venkataraj, Yuanhang Cheng, Daniil Bash, Felipe Oviedo, J. Senthilnath, Vijila Chellappan, Yee-Fun Lim, Armin G. Aberle, Benjamin P. MacLeod, Fraser G. L. Parlane, Curtis P. Berlinguette, Qianxiao Li, Tonio Buonassisi, Zhe Liu
2022	A*	`conf`	Unraveling Model-Agnostic Meta-Learning via The Adaptation Learning Rate. ICLR Yingtian Zou, Fusheng Liu, Qianxiao Li
2021	—	`conf`	A Data Driven Method for Computing Quasipotentials. MSML Bo Lin, Qianxiao Li, Weiqing Ren
2021	A*	`conf`	Adversarial Invariant Learning. CVPR Nanyang Ye, Jingxuan Tang, Huayu Deng, Xiao-Yun Zhou, Qianxiao Li, Zhenguo Li, Guang-Zhong Yang, Zhanxing Zhu
2021	A*	`conf`	Amata: An Annealing Mechanism for Adversarial Training Acceleration. AAAI Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2021	A*	`conf`	Approximation Theory of Convolutional Architectures for Time Series Modelling. ICML Haotian Jiang, Zhong Li, Qianxiao Li
2021	J	`jnl`	Approximation Theory of Convolutional Architectures for Time Series Modelling. CoRR Haotian Jiang, Zhong Li, Qianxiao Li
2021	J	`jnl`	Computing the Invariant Distribution of Randomly Perturbed Dynamical Systems Using Deep Learning. CoRR Bo Lin, Qianxiao Li, Weiqing Ren
2021	J	`jnl`	Distributed optimization for degenerate loss functions arising from over-parameterization. Artif. Intell. Chi Zhang, Qianxiao Li
2021	—	`conf`	Forward and Inverse Approximation Theory for Linear Temporal Convolutional Networks. GSI (2) Haotian Jiang, Qianxiao Li
2021	A*	`conf`	On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. ICLR Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2021	J	`jnl`	Personalized Algorithm Generation: A Case Study in Meta-Learning ODE Integrators. CoRR Yue Guo, Felix Dietrich, Tom Bertalan, Danimir T. Doncevic, Manuel Dahmen, Ioannis G. Kevrekidis, Qianxiao Li
2021	J	`jnl`	QROSS: QUBO Relaxation Parameter Optimisation via Learning Solver Surrogates. CoRR Tian Huang, Siong Thye Goh, Sabrish Gopalakrishnan, Tao Luo, Qianxiao Li, Hoong Chuin Lau
2021	—	`conf`	QROSS: QUBO Relaxation Parameter optimisation via Learning Solver Surrogates. ICDCS Workshops Tian Huang, Siong Thye Goh, Sabrish Gopalakrishnan, Tao Luo, Qianxiao Li, Hoong Chuin Lau
2021	A*	`conf`	Towards Robust Neural Networks via Close-loop Control. ICLR Zhuotong Chen, Qianxiao Li, Zheng Zhang
2021	J	`jnl`	Towards Robust Neural Networks via Close-loop Control. CoRR Zhuotong Chen, Qianxiao Li, Zheng Zhang
2020	J	`jnl`	A Data Driven Method for Computing Quasipotentials. CoRR Bo Lin, Qianxiao Li, Weiqing Ren
2020	J	`jnl`	Amata: An Annealing Mechanism for Adversarial Training Acceleration. CoRR Nanyang Ye, Qianxiao Li, Xiao-Yun Zhou, Zhanxing Zhu
2020	J	`jnl`	Collaborative Inference for Efficient Remote Monitoring. CoRR Chi Zhang, Yong Sheng Soh, Ling Feng, Tianyi Zhou, Qianxiao Li
2020	J	`jnl`	Inverse design of crystals using generalized invertible crystallographic representation. CoRR Zekun Ren, Juhwan Noh, Siyu I. P. Tian, Felipe Oviedo, Guangzong Xing, Qiaohao Liang, Armin Aberle, Yi Liu, Qianxiao Li, Senthilnath Jayavelu, Kedar Hippalgaonkar, Yousung Jung, Tonio Buonassisi
2020	J	`jnl`	On the Curse of Memory in Recurrent Neural Networks: Approximation and Optimization Analysis. CoRR Zhong Li, Jiequn Han, Weinan E, Qianxiao Li
2020	J	`jnl`	OnsagerNet: Learning Stable and Interpretable Dynamics using a Generalized Onsager Principle. CoRR Haijun Yu, Xinyuan Tian, Weinan E, Qianxiao Li
2020	J	`jnl`	Optimising Stochastic Routing for Taxi Fleets with Model Enhanced Reinforcement Learning. CoRR Shen Ren, Qianxiao Li, Liye Zhang, Zheng Qin, Bo Yang
2020	J	`jnl`	Optimization in Machine Learning: A Distribution Space Approach. CoRR Yongqiang Cai, Qianxiao Li, Zuowei Shen
2019	A*	`conf`	A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent. ICML Yongqiang Cai, Qianxiao Li, Zuowei Shen
2019	J	`jnl`	Computing Committor Functions for the Study of Rare Events Using Deep Learning. CoRR Qianxiao Li, Bo Lin, Weiqing Ren
2019	A*	`conf`	Decentralized Optimization with Edge Sampling. IJCAI Chi Zhang, Qianxiao Li, Peilin Zhao
2019	J	`jnl`	Deep Learning via Dynamical Systems: An Approximation Perspective. CoRR Qianxiao Li, Ting Lin, Zuowei Shen
2019	J	`jnl`	Distributed Optimization for Over-Parameterized Learning. CoRR Chi Zhang, Qianxiao Li
2019	J	`jnl`	Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. J. Mach. Learn. Res. Qianxiao Li, Cheng Tai, Weinan E
2018	J	`jnl`	A Mean-Field Optimal Control Formulation of Deep Learning. CoRR Weinan E, Jiequn Han, Qianxiao Li
2018	J	`jnl`	An Emergent Space for Distributed Data With Hidden Internal Order Through Manifold Learning. IEEE Access Felix P. Kemeth, Sindre W. Haugland, Felix Dietrich, Tom Bertalan, Kevin Höhlein, Qianxiao Li, Erik M. Bollt, Ronen Talmon, Katharina Krischer, Ioannis G. Kevrekidis
2018	A*	`conf`	An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks. ICML Qianxiao Li, Shuji Hao
2018	J	`jnl`	An Optimal Control Approach to Deep Learning and Applications to Discrete-Weight Neural Networks. CoRR Qianxiao Li, Shuji Hao
2018	J	`jnl`	Dynamics of Taxi-like Logistics Systems: Theory and Microscopic Simulations. CoRR Bo Yang, Qianxiao Li
2018	J	`jnl`	Machine learning enables polymer cloud-point engineering via inverse design. CoRR Jatin Nitin Kumar, Qianxiao Li, Karen Y. T. Tang, Tonio Buonassisi, Anibal L. Gonzalez-Oyarce, Jun Ye
2018	J	`jnl`	On Matching, and Even Rectifying, Dynamical Systems through Koopman Operator Eigenfunctions. SIAM J. Appl. Dyn. Syst. Erik M. Bollt, Qianxiao Li, Felix Dietrich, Ioannis G. Kevrekidis
2018	J	`jnl`	On the Convergence and Robustness of Batch Normalization. CoRR Yongqiang Cai, Qianxiao Li, Zuowei Shen
2018	J	`jnl`	Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations. CoRR Qianxiao Li, Cheng Tai, Weinan E
2018	B	`conf`	Turn-by-turn Intelligent Manoeuvring of Driverless Taxis: A Recursive Value Model Enhanced by Reinforcement Learning. Intelligent Vehicles Symposium Bo Yang, Qianxiao Li
2017	J	`jnl`	Maximum Principle Based Algorithms for Deep Learning. CoRR Qianxiao Li, Long Chen, Cheng Tai, Weinan E
2017	J	`jnl`	Maximum Principle Based Algorithms for Deep Learning. J. Mach. Learn. Res. Qianxiao Li, Long Chen, Cheng Tai, Weinan E
2017	A*	`conf`	Stochastic Modified Equations and Adaptive Stochastic Gradient Algorithms. ICML Qianxiao Li, Cheng Tai, Weinan E
2016	—	`conf`	Noisy Hegselmann-Krause systems: Phase transition and the 2R-conjecture. CDC Chu Wang, Qianxiao Li, Weinan E, Bernard Chazelle
2015	J	`jnl`	Dynamics of Stochastic Gradient Algorithms. CoRR Qianxiao Li, Cheng Tai, Weinan E