A Theory of Non-Acyclic Generative Flow Networks. - Leo Maxime Brunswic; Yinchuan Li; Yushun Xu; Shangling Jui; Lizhuang Ma (CoRR, 2023)

A Theory of Non-acyclic Generative Flow Networks. - Leo Maxime Brunswic; Yinchuan Li; Yushun Xu; Yijun Feng; Shangling Jui; Lizhuang Ma (AAAI, 2024)

Parametric Feature Transfer: One-shot Federated Learning with Foundation Models. - Mahdi Beitollahi; Alex Bie; Sobhan Hemati; Leo Maxime Brunswic; Xu Li 001; Xi Chen 009; Guojun Zhang (CoRR, 2024)

NoT: Federated Unlearning via Weight Negation. - Yasser H. Khalil; Leo Maxime Brunswic; Soufiane Lamghari; Xu Li 001; Mahdi Beitollahi; Xi Chen 009 (CVPR, 2025)

Foundation Models Meet Federated Learning: A One-shot Feature-sharing Method with Privacy and Performance Guarantees. - Mahdi Beitollahi; Alex Bie; Sobhan Hemati; Leo Maxime Brunswic; Xu Li 001; Xi Chen 009; Guojun Zhang (Trans. Mach. Learn. Res., 2025)

Generative Models in Decision Making: A Survey. - Yinchuan Li; Xinyu Shao; Jianping Zhang; Haozhi Wang; Leo Maxime Brunswic; Kaiwen Zhou; Jiqian Dong; Kaiyang Guo; Xiu Li 001; Zhitang Chen; Jun Wang 012; Jianye Hao (CoRR, 2025)

Ergodic Generative Flows. - Leo Maxime Brunswic; Mateo Clemente; Rui Heng Yang; Adam Sigal; Amir Rasouli; Yinchuan Li (CoRR, 2025)