Publications

Preprints

  • S. Tong, J. Hu, F. Li, Z. Shen, Y. Yang, & J. Yu (2026). Reduced Order Model for Parametric Boltzmann Equation and its Application to Inverse Problems. arXiv:2609.02578. [arXiv]

  • J. Yu, J. Hu, F. Li, S. Tong, Y. Yang, & Z. Shen (2026). Structure-Preserving Reduced-Order Modeling via Low-Rank Transport Signatures. arXiv:2607.01696. [arXiv]

  • J. Yu, X. Cheng, J.-G. Liu, & H. Zhao (2024). Convergence Analysis and Acceleration of Fictitious Play for General Mean-Field Games via the Best Response. arXiv:2411.07989. [arXiv]

  • Y. Liu, W. Peng, T. Wang, & J. Yu (2024). Zeroth-order Stochastic Cubic Newton Method Revisited. arXiv:2410.22357. [arXiv]

  • T. Wang, Z. Wang, & J. Yu (2024). Zeroth-order Low-Rank Hessian Estimation via Matrix Recovery. arXiv:2402.05385. [arXiv]

Journal Articles

  • H. Huang, J. Yu, T. Chen, & R. Lai (2026). Joint Inference of Trajectory and Obstacle in Mean-Field Games via Bilevel Optimization. Journal of Scientific Computing, 109, 5. [paper]

  • J. Yu, J.-G. Liu, & H. Zhao (2025). Equilibrium Correction Iteration for A Class of Mean-Field Game Inverse Problems. Inverse Problems, 41, 125009. [paper] [code]

  • J. Yu, Q. Xiao, T. Chen, & R. Lai (2024). A Bilevel Optimization Method for Inverse Mean-Field Games. Inverse Problems, 40, 105016. [paper] [code]

  • J. Yu, R. Lai, W. Li, & S. Osher (2024). A Fast Proximal Gradient Method and Convergence Analysis for Dynamic Mean Field Planning. Mathematics of Computation, 93, 603–642. [paper] [code]

  • H. Huang, J. Yu, J. Chen, & R. Lai (2023). Bridging Mean-Field Games and Normalizing Flows with Trajectory Regularization. Journal of Computational Physics, 487, 112155. [paper] [code]

  • J. Yu, R. Lai, W. Li, & S. Osher (2023). Computational Mean-Field Games on Manifolds. Journal of Computational Physics, 484, 112070. [paper] [code]

Conference Papers