Fei Lu - RankMe

34 papers Journal 33Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning Multi-type heterogeneous interacting particle systems. CoRR Quanjun Lang, Xiong Wang, Fei Lu, Mauro Maggioni
2025	J	`jnl`	Dimension-Free Minimax Rates for Learning Pairwise Interactions in Attention-Style Models. CoRR Shai Zucker, Xiong Wang, Fei Lu, Inbar Seroussi
2025	J	`jnl`	Robust First- and Second-Order Differentiation for Regularized Optimal Transport. SIAM J. Sci. Comput. Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2025	J	`jnl`	Transformer learns the cross-task prior and regularization for in-context learning. CoRR Fei Lu, Yue Yu
2024	J	`jnl`	A Data-Adaptive RKHS Prior for Bayesian Learning of Kernels in Operators. J. Mach. Learn. Res. Neil K. Chada, Quanjun Lang, Fei Lu, Xiong Wang
2024	J	`jnl`	Interacting Particle Systems on Networks: joint inference of the network and the interaction kernel. CoRR Quanjun Lang, Xiong Wang, Fei Lu, Mauro Maggioni
2024	J	`jnl`	Robust First and Second-Order Differentiation for Regularized Optimal Transport. CoRR Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2024	J	`jnl`	Self-test loss functions for learning weak-form operators and gradient flows. CoRR Yuan Gao, Quanjun Lang, Fei Lu
2023	J	`jnl`	Benchmarking optimality of time series classification methods in distinguishing diffusions. CoRR Zehong Zhang, Fei Lu, Esther Xu Fei, Terry Lyons, Yannis G. Kevrekidis, Tom Woolf
2023	J	`jnl`	NySALT: Nyström-type inference-based schemes adaptive to large time-stepping. J. Comput. Phys. Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2023	J	`jnl`	Small noise analysis for Tikhonov and RKHS regularizations. CoRR Quanjun Lang, Fei Lu
2022	J	`jnl`	A Data-Adaptive Prior for Bayesian Learning of Kernels in Operators. CoRR Neil K. Chada, Quanjun Lang, Fei Lu, Xiong Wang
2022	—	`conf`	Data adaptive RKHS Tikhonov regularization for learning kernels in operators. MSML Fei Lu, Quanjun Lang, Qingci An
2022	J	`jnl`	Data adaptive RKHS Tikhonov regularization for learning kernels in operators. CoRR Fei Lu, Quanjun Lang, Qingci An
2022	J	`jnl`	Learning Interaction Kernels in Mean-Field Equations of First-Order Systems of Interacting Particles. SIAM J. Sci. Comput. Quanjun Lang, Fei Lu
2022	J	`jnl`	Learning Interaction Kernels in Stochastic Systems of Interacting Particles from Multiple Trajectories. Found. Comput. Math. Fei Lu, Mauro Maggioni, Sui Tang
2022	J	`jnl`	Nonparametric learning of kernels in nonlocal operators. CoRR Fei Lu, Qingci An, Yue Yu
2022	J	`jnl`	NySALT: Nyström-type inference-based schemes adaptive to large time-stepping. CoRR Xingjie Li, Fei Lu, Molei Tao, Felix X.-F. Ye
2022	J	`jnl`	Stochastic Data-Driven Variational Multiscale Reduced Order Models. CoRR Fei Lu, Changhong Mou, Honghu Liu, Traian Iliescu
2022	J	`jnl`	Unsupervised learning of observation functions in state-space models by nonparametric moment methods. CoRR Qingci An, Yannis G. Kevrekidis, Fei Lu, Mauro Maggioni
2021	J	`jnl`	Cluster Prediction for Opinion Dynamics From Partial Observations. IEEE Trans. Signal Inf. Process. over Networks Zehong Zhang, Fei Lu
2021	J	`jnl`	Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism. J. Comput. Phys. Kevin K. Lin, Fei Lu
2021	J	`jnl`	ISALT: Inference-based schemes adaptive to large time-stepping for locally Lipschitz ergodic systems. CoRR Xingjie Li, Fei Lu, Felix X.-F. Ye
2021	J	`jnl`	Identifiability of interaction kernels in mean-field equations of interacting particles. CoRR Quanjun Lang, Fei Lu
2021	J	`jnl`	Learning interaction kernels in heterogeneous systems of agents from multiple trajectories. J. Mach. Learn. Res. Fei Lu, Mauro Maggioni, Sui Tang
2021	J	`jnl`	Shock trace prediction by reduced models for a viscous stochastic Burgers equation. CoRR Nan Chen, Honghu Liu, Fei Lu
2020	J	`jnl`	Data-Driven Model Reduction for Stochastic Burgers Equations. Entropy Fei Lu
2020	J	`jnl`	Data-driven model reduction for stochastic Burgers equations. CoRR Fei Lu
2020	J	`jnl`	Learning interaction kernels in mean-field equations of 1st-order systems of interacting particles. CoRR Quanjun Lang, Fei Lu
2020	J	`jnl`	On the coercivity condition in the learning of interacting particle systems. CoRR Zhongyang Li, Fei Lu
2019	J	`jnl`	Data-driven model reduction, Wiener projections, and the Mori-Zwanzig formalism. CoRR Kevin K. Lin, Fei Lu
2019	J	`jnl`	Learning interaction kernels in heterogeneous systems of agents from multiple trajectories. CoRR Fei Lu, Mauro Maggioni, Sui Tang
2018	J	`jnl`	Nonparametric inference of interaction laws in systems of agents from trajectory data. CoRR Fei Lu, Mauro Maggioni, Sui Tang, Ming Zhong
2015	J	`jnl`	Limitations of polynomial chaos expansions in the Bayesian solution of inverse problems. J. Comput. Phys. Fei Lu, Matthias Morzfeld, Xuemin Tu, Alexandre J. Chorin