1. Akiba, T., Sano, S., Yanase, T., Ohta, T., & Koyama, M. (2019). Optuna: A next-generation hyperparameter optimization framework. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining (pp. 2623–2631).
2. Bergstra, J., Bardenet, R., Bengio, Y., & Kégl, B. (2011). Algorithms for Hyper-Parameter Optimization. In Advances in neural information processing systems 24: 25th annual conference on neural information processing systems 2011. proceedings of a meeting held 12-14 December 2011, granada, Spain (pp. 2546–2554).
3. Bo, D., Hu, B., Wang, X., Zhang, Z., Shi, C., & Zhou, J. (2022). Regularizing graph neural networks via consistency-diversity graph augmentations. vol. 36, In Proceedings of the AAAI conference on artificial intelligence (pp. 3913–3921).
4. Bruna, J., Zaremba, W., Szlam, A., & LeCun, Y. (2014). Spectral Networks and Locally Connected Networks on Graphs. In International conference on learning representations.
5. Towards sparse hierarchical graph classifiers;Cangea,2018