Learning Theory of Deep Structured Neural Networks

  • ZHOU, Xiang (Principal Investigator / Project Coordinator)

Project: Research

  • 7 RGC 21 - Publication in refereed journal
  • 2 RGC 32 - Refereed conference paper (with host publication)
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RGC 32 - Refereed conference paper (with host publication)

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  • 2023

    Roughness Index for Loss Landscapes of Neural Network Models of Partial Differential Equations

    Wu, K., Jian, X., Du, R., Chen, J. & ZHOU, X., Dec 2023, Proceedings - 2023 IEEE International Conference on Big Data. He, J., Palpanas, T., Hu, X., Cuzzocrea, A. & Dou, D. (eds.). IEEE, p. 966-975 (Proceedings - IEEE International Conference on Big Data, BigData).

    Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

  • 2022

    Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network

    Han, J., Cai, Z., Wu, Z. & Zhou, X., Dec 2022, Proceedings - 2022 IEEE International Conference on Big Data. Tsumoto, S., Ohsawa, Y., Van den Poel, D., Hu, X., Motomura, Y., Takagi, T., Wu, L., Xie, Y., Abe, A. & Raghavan, V. (eds.). IEEE, p. 921-930 (Proceedings - IEEE International Conference on Big Data, Big Data).

    Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

    5 Citations (Scopus)