1 code implementation • 21 Nov 2023 • Zhang Zhang, Ruyi Tao, Jiang Zhang
The rapid increase in the parameters of deep learning models has led to significant costs, challenging computational efficiency and model interpretability.
1 code implementation • 25 Apr 2022 • Zhang Zhang, Ruyi Tao, Yongzai Tao, Mingze Qi, Jiang Zhang
And experiments show that our model perform better on a network with higher Reachable CC.
1 code implementation • 30 Dec 2018 • Zhang Zhang, Yi Zhao, Jing Liu, Shuo Wang, Ruyi Tao, Ruyue Xin, Jiang Zhang
We exhibit the universality of our framework on different kinds of time-series data: with the same structure, our model can be trained to accurately recover the network structure and predict future states on continuous, discrete, and binary dynamics, and outperforms competing network reconstruction methods.