Incorporating symbolic domain knowledge into graph neural networks

Author:

Dash TirtharajORCID,Srinivasan Ashwin,Vig Lovekesh

Funder

Science and Engineering Research Board

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference61 articles.

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2. Ando, H. Y., Dehaspe, L., Luyten, W., Van Craenenbroeck, E., Vandecasteele, H., & Van Meervelt, L. (2006). Discovering h-bonding rules in crystals with inductive logic programming. Molecular pharmaceutics, 3(6), 665–674.

3. Barceló, P., Kostylev, E. V., Monet, M., Pérez, J., Reutter, J., & Silva, J. P. (2020). The logical expressiveness of graph neural networks. In International Conference on Learning Representations, https://openreview.net/forum?id=r1lZ7AEKvB

4. Baskin, I. I., Palyulin, V. A., & Zefirov, N. S. (1997). A neural device for searching direct correlations between structures and properties of chemical compounds. Journal of Chemical Information and Computer Sciences, 37(4), 715–721.

5. Besold, T. R., Garcez, A. d., Bader, S., Bowman, H., Domingos, P., Hitzler, P., Kühnberger, K. U., Lamb, L. C., Lowd, D., & Lima, P.M.V., et al. (2017). Neural-symbolic learning and reasoning: A survey and interpretation. arXiv preprint arXiv:1711.03902

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