OT-net: a reusable neural optimal transport solver

Author:

Li Zezeng,Li Shenghao,Jin Lianbao,Lei NaORCID,Luo Zhongxuan

Funder

National Key R &D Program of China

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Reference69 articles.

1. Abbasnejad, M. E., Shi, Q., Abbasnejad, I., Hengel, A. V. D., & Dick, A. (2017). Bayesian conditional generative adverserial networks. arXiv:1706.05477.

2. Alexandrov, A. D. (2005). Convex polyhedra (Vol. 109). Springer.

3. Alvarez-Melis, D., Jaakkola, T., & Jegelka, S. (2018). Structured optimal transport. In International Conference on Artificial Intelligence and Statistics, pp. 1771–1780

4. An, D. et al. (2019). Ae-ot: A new generative model based on extended semi-discrete optimal transport. In ICLR 2020.

5. An, D., Lei, N., Xu, X., & Gu, X. (2022). Efficient optimal transport algorithm by accelerated gradient descent. Proceedings of the AAAI Conference on Artificial Intelligence, 36, 10119–10128.

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