Samy Wu Fung

Samy Wu Fung

Assistant Professor of Applied Mathematics

Preprints/Submitted Articles

  1. Wu Fung S, Berkels B. A Generalization Bound for a Family of Implicit Networks. arXiv:2410.07427, 2024.
  2. Knutson B, Chyba A, Ivanitskiy M, Pettyjohn J, Diniz-Behn C, Wu Fung S, McKenzie D. On Logical Extrapolation for Mazes with Recurrent and Implicit Networks . arXiv:2410.03020, 2024.
  3. Wu Fung S, Nurbekyan L. Mean-Field Control Barrier Functions: A Framework for Real-Time Swarm Control. arXiv:2409.18945, 2024.
  4. Terrab S, Wu Fung S, Ryan JK. A hybrid SIAC -- data-driven post-processing filter for discontinuities in solutions to numerical PDEs. arXiv:2408.05193, 2024.
  5. Parada R, Wu Fung S, Osher S. Fast Partial Fourier Transforms for Large-Scale Ptychography. arXiv:2408.03532, 2024.
  6. Tibshirani R, Wu Fung S, Heaton H, Osher S. Laplace Meets Moreau: Smooth Approximation to Infimal Convolutions Using Laplace's Method. arXiv:2406.02003, 2024.
  7. Vidal A, Wu Fung S, Tenorio L, Osher S, Nurbekyan L. Kernel Expansions for High-Dimensional Mean-Field Control with Non-local Interactions. arXiv:2405.10922, 2024.
  8. Ivanitskiy MI, Shah R, Spies AF, Räuker T, Valentine D, Rager C, Quirke L, Mathwin C, Corlouer G, Diniz-Behn C, Wu Fung S. A Configurable Library for Generating and Manipulating Maze Datasets. arXiv:2309.10498, 2023.

Published/Accepted Articles

  1. McKenzie D, Wu Fung S, Heaton H. Differentiating Through Integer Linear Programs with Quadratic Regularization and Davis-Yin Splitting, Transactions on Machine Learning Research, accepted, 2024.
  2. McKenzie D, Heaton H, Li Q, Wu Fung S, W Yin, S Osher. Three-Operator Splitting for Learning to Predict Equilibria in Convex Games, SIAM Journal on Mathematics of Data Science, accepted, 2024.
  3. Ivanitskiy MI, Spies AF, Räuker T, Corlouer G, Mathwin C, Quirke L, Rager C, Shah R, Valentine D, Diniz-Behn C, Katsumi I, Wu Fung S. Structured World Representations in Maze-Solving Transformers, NeurIPS Workshop on Unifying Representations in Neural Models, 2023.
  4. Heaton H, Wu Fung S. Explainable AI via Learning to Optimize, Scientific Reports, 13 (10103). 2023.
  5. Vidal A, Wu Fung S, Tenorio L, Osher S, Nurbekyan L. Taming Hyperparameter Tuning in Continuous Normalizing Flows Using the JKO Scheme, Scientific Reports, 13 (1). 2023.
  6. Osher S, Heaton H, Wu Fung S. A Hamilton-Jacobi-based Proximal Operator, Proceedings of the National Academy of Sciences, 120 (14), e2220469120. 2023.
  7. Heaton H, Wu Fung S, Osher S. Global Solutions to Nonconvex Problems by Evolution of Hamilton-Jacobi PDEs, Communications in Applied Mathematics and Computation, 1-21. 2023.
  8. Chow YT, Wu Fung S, Liu S, Nurbekyan L, Osher S. A Numerical Algorithm for Inverse Problem from Partial Boundary Measurement Arising from Mean Field Game Problem, Inverse Problems, 39(1), 014001. 2022.
  9. Agrawal A, Lee W, Wu Fung S, Nurbekyan L. Random Features for High-Dimensional Nonlocal Mean-Field Games, Journal of Computational Physics, 459, pp. 111136. 2022.
  10. Onken D, Nurbekyan L, Li X, Wu Fung S, Osher S, Ruthotto L. A Neural Network Approach for Real-Time High-Dimensional Optimal Control, IEEE Transactions on Control Systems Technology, 31(1), 235-251. 2022.
  11. Wu Fung S, Heaton H, Li Q, McKenzie D, Osher S, Yin W. JFB: Jacobian-free Backpropagation for Implicit Networks, AAAI Conference on Artificial Intelligence, 36(6), 6648-6656. 2022.
  12. Ye J, Wan C, Wu Fung S. Adaptive Uncertainty-Weighted ADMM for Distributed Optimization, Journal of Applied and Numerical Optimization, pp. 273-290. 2022.
  13. Heaton H, Wu Fung S, Lin AT, Osher S, Yin W. Wasserstein-based Projections with Applications to Inverse Problems, SIAM Journal on Mathematics of Data Science, 40(2), 581-603, 2022.
  14. Heaton H, Wu Fung S, Gibali A, Yin W. Feasibility-based Fixed Point Networks, Fixed Point Theory and Algorithms for Sciences and Engineering, 21. 2021.
  15. Kan K, Wu Fung S, Ruthotto L. PNKH-B: A Projected Newton-Krylov Method for Large-Scale Bound-Constrained Optimization, SIAM Journal on Scientific Computing, 43(5), pp. S704-S726. 2021.
  16. Onken D, Nurbekyan L, Li X, Wu Fung S, Osher S, Ruthotto L. A Neural Network Approach Applied to Multi-Agent Optimal Control, European Control Conference 2021 (ECC21), pp. 1036-1041. 2021.
  17. Lin AT, Wu Fung S, Li W, Nurbekyan L, Osher S. Alternating the Population and Agent Control via Two Neural Networks to Solve High-Dimensional Stochastic Mean Field Games, Proceedings of the National Academy of Sciences, 118(31). 2021.
  18. Onken D, Wu Fung S, Li X, Ruthotto L. OT-Flow: Fast and Accurate Continuous Normalizing Flows via Optimal Transport, AAAI Conference on Artificial Intelligence, 35(10), 9223-9232. 2021.
  19. Ruthotto L, Osher S, Li W, Nurbekyan L, Wu Fung S. A Machine Learning Framework for Solving High-Dimensional Mean Field Game and Mean Field Control Problems, Proceedings of the National Academy of Sciences, 117(17), 9183-9193. 2020.
  20. Wu Fung S, Tyrväinen S, Ruthotto L, Haber E. ADMM-Softmax: An ADMM Approach for Multinomial Logistic Regression, Electronic Transactions on Numerical Analysis, 52, 214-229. 2020.
  21. Wu Fung S, Di Z. Multigrid Optimization for Large-Scale Ptychographic Phase Retrieval, SIAM Journal on Imaging Sciences, 13(1), 214–233. 2020.
  22. Wu Fung S, Ruthotto L. An Uncertainty-Weighted Asynchronous ADMM Method for Parallel PDE Parameter Estimation, SIAM Journal on Scientific Computing, 41(5), S129-S148. 2019.
  23. Wu Fung S, Ruthotto L. A Multiscale Method for Model Order Reduction in PDE Parameter Estimation, Journal of Computational and Applied Mathematics, 350, 19-34. 2019.