1. P. W. Battaglia , J. B. Hamrick , V. Bapst , A. Sanchez-Gonzalez , V. Zambaldi , M. Malinowski , A. Tacchetti , D. Raposo , A. Santoro , R. Faulkner , Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261 , 2018 . P. W. Battaglia, J. B. Hamrick, V. Bapst, A. Sanchez-Gonzalez, V. Zambaldi, M. Malinowski, A. Tacchetti, D. Raposo, A. Santoro, R. Faulkner, et al. Relational inductive biases, deep learning, and graph networks. arXiv preprint arXiv:1806.01261, 2018.
2. J. Chen , X. Xu , Y. Wu , and H. Zheng . Gc-lstm: Graph convolution embedded lstm for dynamic link prediction. In arXiv preprint arXiv:1812.04206 , 2018 . J. Chen, X. Xu, Y. Wu, and H. Zheng. Gc-lstm: Graph convolution embedded lstm for dynamic link prediction. In arXiv preprint arXiv:1812.04206, 2018.
3. J. Chung , C. Gulcehre , K. Cho , and Y. Bengio . Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 , 2014 . J. Chung, C. Gulcehre, K. Cho, and Y. Bengio. Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555, 2014.
4. M. Defferrard , X. Bresson , and P. Vandergheynst . Convolutional neural networks on graphs with fast localized spectral filtering . Advances in Neural Information Processing Systems (NeurIPS) , 2016 . M. Defferrard, X. Bresson, and P. Vandergheynst. Convolutional neural networks on graphs with fast localized spectral filtering. Advances in Neural Information Processing Systems (NeurIPS), 2016.
5. Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting