Publications
Preprints
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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]
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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]
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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]
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Y. Liu, W. Peng, T. Wang, & J. Yu (2024). Zeroth-order Stochastic Cubic Newton Method Revisited.
arXiv:2410.22357.
[arXiv]
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T. Wang, Z. Wang, & J. Yu (2024). Zeroth-order Low-Rank Hessian Estimation via Matrix Recovery.
arXiv:2402.05385.
[arXiv]
Journal Articles
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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]
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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]
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J. Yu, Q. Xiao, T. Chen, & R. Lai (2024). A Bilevel Optimization Method for Inverse Mean-Field Games.
Inverse Problems, 40, 105016.
[paper]
[code]
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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]
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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]
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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
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