Connecting GANs and MFGs. - Haoyang Cao; Xin Guo 001; Mathieu Laurière (CoRR, 2020)

Approximation and convergence of GANs training: an SDE approach. - Haoyang Cao; Xin Guo 001 (CoRR, 2020)

Identifiability in inverse reinforcement learning. - Haoyang Cao; Samuel N. Cohen; Lukasz Szpruch (NeurIPS, 2021)

Generative Adversarial Network: Some Analytical Perspectives. - Haoyang Cao; Xin Guo 001 (CoRR, 2021)

Meta-learning with GANs for anomaly detection, with deployment in high-speed rail inspection system. - Haoyang Cao; Xin Guo 001; Guan Wang (CoRR, 2022)

Towards mapping the contemporary art world with ArtLM: an art-specific NLP model. - Qinkai Chen; Mohamed El-Mennaoui; Antoine Fosset; Amine Rebei; Haoyang Cao; Philine Bouscasse; Christy Eóin O'Beirne; Sasha Shevchenko; Mathieu Rosenbaum (CoRR, 2022)

Nonzero-Sum Stochastic Games and Mean-Field Games with Impulse Controls. - Matteo Basei; Haoyang Cao; Xin Guo 001 (Math. Oper. Res., 2022)

Feasibility and Transferability of Transfer Learning: A Mathematical Framework. - Haoyang Cao; Haotian Gu; Xin Guo 001; Mathieu Rosenbaum (CoRR, 2023)

Feasibility of Transfer Learning: A Mathematical Framework. - Haoyang Cao; Haotian Gu; Xin Guo 001 (CoRR, 2023)

Transfer Learning for Portfolio Optimization. - Haoyang Cao; Haotian Gu; Xin Guo 001; Mathieu Rosenbaum (CoRR, 2023)

Risk of Transfer Learning and its Applications in Finance. - Haoyang Cao; Haotian Gu; Xin Guo 001; Mathieu Rosenbaum (CoRR, 2023)

Stationary Discounted and Ergodic Mean Field Games with Singular Controls. - Haoyang Cao; Jodi Dianetti; Giorgio Ferrari (Math. Oper. Res., 2023)

Inference of Utilities and Time Preference in Sequential Decision-Making. - Haoyang Cao; Zhengqi Wu; Renyuan Xu (CoRR, 2024)

Stochastic differential equation approximations of generative adversarial network training and its long-run behavior. - Haoyang Cao; Xin Guo 001 (J. Appl. Probab., 2024)

Connecting GANs, Mean-Field Games, and Optimal Transport. - Haoyang Cao; Xin Guo 001; Mathieu Laurière (SIAM J. Appl. Math., 2024)