1. Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al., 2016. {TensorFlow}: a system for {Large-Scale} machine learning. In: 12th USENIX Symposium on Operating Systems Design and Implementation. OSDI 16, pp. 265–283.
2. Amershi, S., Begel, A., Bird, C., DeLine, R., Gall, H., Kamar, E., Nagappan, N., Nushi, B., Zimmermann, T., 2019. Software engineering for machine learning: A case study. In: 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice. ICSE-SEIP.
3. Continuously reproducing toolchains in pattern recognition and machine learning experiments;Anjos,2017
4. Baylor, D., Breck, E., Cheng, H.-T., Fiedel, N., Foo, C., Haque, Z., Haykal, S., Ispir, M., Jain, V., Koc, L., et al., 2017. Tfx: A tensorflow-based production-scale machine learning platform. In: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. pp. 1387–1395.
5. Artificial intelligence for the early design phases of space missions;Berquand,2019