1. Buterez, D., Janet, J.P., Kiddle, S.J., Oglic, D., Liò, P.: Graph neural networks with adaptive readouts. In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A. (eds.) Advances in Neural Information Processing Systems, vol. 35, pp. 19746–19758. Curran Associates, Inc. (2022)
2. Chen, Y., Ma, T., Yang, X., Wang, J., Song, B., Zeng, X.: MUFFIN: multi-scale feature fusion for drug-drug interaction prediction. Bioinformatics 37(17), 2651–2658 (2021)
3. Chung, J., Gulcehre, C., Cho, K., Bengio, Y.: Empirical evaluation of gated recurrent neural networks on sequence modeling. arXiv preprint arXiv:1412.3555 (2014)
4. Corso, G., Cavalleri, L., Beaini, D., Liò, P., Veličković, P.: Principal neighbourhood aggregation for graph nets. Adv. Neural. Inf. Process. Syst. 33, 13260–13271 (2020)
5. Deng, Y., Xu, X., Qiu, Y., Xia, J., Zhang, W., Liu, S.: A multimodal deep learning framework for predicting drug-drug interaction events. Bioinformatics 36(15), 4316–4322 (2020)