3 citations · 5 across the 6 of their papers we have counts for
6 papers
When Rough Data Helps: A Phase Transition in Convergence Rates for Kernel Recovery in Integral Operators
Jihong Wang, Fei Lu, Yue Yu
Learning kernels in operators from data is a fundamental task that arises in nonlocal continuum mechanics, operator learning, and interacting particle systems. A central question i…
Learning Lévy density via adaptive RKHS regression with bi-level optimization
Luxuan Yang, Fei Lu, Ting Gao +2
We propose a nonparametric method to learn the Lévy density from probability density data governed by a nonlocal Fokker-Planck equation. We recast the problem as identifying the ke…
Transformer learns the cross-task prior and regularization for in-context learning
Fei Lu, Yue Yu
Transformers have shown a remarkable ability for in-context learning (ICL), making predictions based on contextual examples. However, while theoretical analyses have explored this…
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery
Yue Yu, Ning Liu, Fei Lu +3
Despite the recent popularity of attention-based neural architectures in core AI fields like natural language processing (NLP) and computer vision (CV), their potential in modeling…
Robust First and Second-Order Differentiation for Regularized Optimal Transport
Xingjie Li, Fei Lu, Molei Tao +1
Applications such as unbalanced and fully shuffled regression can be approached by optimizing regularized optimal transport (OT) distances, such as the entropic OT and Sinkhorn dis…
MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data
Meng Fang, Xiangpeng Wan, Fei Lu +2
Large language models (LLMs) have significantly advanced natural language understanding and demonstrated strong problem-solving abilities. Despite these successes, most LLMs still…