Wang, Zhongjian, Xin, Jack, and Zhang, Zhiwen. DeepParticle: Learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method. Retrieved from https://par.nsf.gov/biblio/10339336. Journal of Computational Physics 464.C Web. doi:10.1016/j.jcp.2022.111309.

Wang, Zhongjian, Xin, Jack, & Zhang, Zhiwen. DeepParticle: Learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method. Journal of Computational Physics, 464 (C). Retrieved from https://par.nsf.gov/biblio/10339336. https://doi.org/10.1016/j.jcp.2022.111309

Wang, Zhongjian, Xin, Jack, and Zhang, Zhiwen. "DeepParticle: Learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method". Journal of Computational Physics 464 (C). Country unknown/Code not available. https://doi.org/10.1016/j.jcp.2022.111309. https://par.nsf.gov/biblio/10339336.

@article{osti_10339336,
place = {Country unknown/Code not available}, title = {DeepParticle: Learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method}, url = {https://par.nsf.gov/biblio/10339336}, DOI = {10.1016/j.jcp.2022.111309}, abstractNote = {}, journal = {Journal of Computational Physics}, volume = {464}, number = {C}, author = {Wang, Zhongjian and Xin, Jack and Zhang, Zhiwen}, }