most citedWorst-case generation via minimax optimization in Wasserstein space

1 citations · 2 across the 3 of their papers we have counts for

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7 papers

stat.ML20251 cited

Worst-case generation via minimax optimization in Wasserstein space

Xiuyuan Cheng, Yao Xie, Linglingzhi Zhu +1

Worst-case generation plays a critical role in evaluating robustness and stress-testing systems under distribution shifts, in applications ranging from machine learning models to p…

stat.ML20251 cited

High-dimensional Mean-Field Games by Particle-based Flow Matching

Jiajia Yu, Junghwan Lee, Yao Xie +1

Mean-field games (MFGs) study the Nash equilibrium of systems with a continuum of interacting agents, which can be formulated as the fixed-point of optimal control problems. They p…

stat.ML2025

Deep spatio-temporal point processes: Advances and new directions

Xiuyuan Cheng, Zheng Dong, Yao Xie

Spatio-temporal point processes (STPPs) model discrete events distributed in time and space, with important applications in areas such as criminology, seismology, epidemiology, and…

cs.LG2025

Flow-based generative models as iterative algorithms in probability space

Yao Xie, Xiuyuan Cheng

Generative AI (GenAI) has revolutionized data-driven modeling by enabling the synthesis of high-dimensional data across various applications, including image generation, language m…

math.OC2024

Convergence Analysis and Acceleration of Fictitious Play for General Mean-Field Games via the Best Response

Jiajia Yu, Xiuyuan Cheng, Jian-Guo Liu +1

A mean-field game (MFG) seeks the Nash Equilibrium of a game involving a continuum of players, where the Nash Equilibrium corresponds to a fixed point of the best-response mapping.…

stat.ML2024

Point processes with event time uncertainty

Xiuyuan Cheng, Tingnan Gong, Yao Xie

Point processes are widely used statistical models for continuous-time discrete event data, such as medical records, crime reports, and social network interactions, to capture the…