1. Aggarwal, C.C., Bar-Noy, A., Shamoun, S.: On sensor selection in linked information networks. Comput. Networks 126, 100–113 (2017). https://doi.org/10.1016/j.comnet.2017.05.024
2. Allamanis, M.: The adverse effects of code duplication in machine learning models of code. In: Masuhara, H., Petricek, T. (eds.) Proceedings of the 2019 ACM SIGPLAN International Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software, Onward! 2019, Athens, Greece, 23–24 October 2019, pp. 143–153. ACM (2019). https://doi.org/10.1145/3359591.3359735
3. Babai, L., Kucera, L.: Canonical labelling of graphs in linear average time. In: 20th Annual Symposium on Foundations of Computer Science, San Juan, Puerto Rico, 29–31 October 1979, pp. 39–46. IEEE Computer Society (1979). https://doi.org/10.1109/SFCS.1979.8
4. Backstrom, L., Leskovec, J.: Supervised random walks: predicting and recommending links in social networks. In: King, I., Nejdl, W., Li, H. (eds.) Proceedings of the Forth International Conference on Web Search and Web Data Mining, WSDM 2011, Hong Kong, China, 9–12 February, 2011, pp. 635–644. ACM (2011). https://doi.org/10.1145/1935826.1935914
5. Battaglia, P.W., Pascanu, R., Lai, M., Rezende, D.J., Kavukcuoglu, K.: Interaction networks for learning about objects, relations and physics. In: Lee, D.D., Sugiyama, M., von Luxburg, U., Guyon, I., Garnett, R. (eds.) Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 5–10 December 2016, Barcelona, Spain, pp. 4502–4510 (2016). https://proceedings.neurips.cc/paper/2016/hash/3147da8ab4a0437c15ef51a5cc7f2dc4-Abstract.html