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Graph neural networks (GNNs) have found application for learning in the space of algorithms.
Maximal flow through a network
Ford, L. R. and Fulkerson, D. R · 1956
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On a routing problem
Bellman, R · 1958
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Principal neighbourhood aggregation for graph nets
Corso, G., Cavalleri, L., Beaini, D., Liò, P., and Veličković, P · 2004
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Graph cuts and efficient N-D image segmentation
Boykov, Y. and Funka-Lea, G · 2006
Earlier work this paper cites.
Introduction to Algorithms, 3rd Edition
Cormen, T. H., Leiserson, C. E., Rivest, R. L., and Stein, C · 2009
Cited alongside, same era.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
Cited alongside, same era.
Neural message passing for quantum chemistry
Gilmer, J., Schoenholz, S. S., Riley, P. F., Vinyals, O., and Dahl, G. E · 2017
Cited alongside, same era.
Relational inductive bias for physical construction in humans and machines
Hamrick, J. B., Allen, K. R., Bapst, V., Zhu, T., McKee, K. R., Tenenbaum, J., and Battaglia, P. W · 2018
Cited alongside, same era.
Neural execution of graph algorithms
Veličković, P., Ying, R., Padovano, M., Hadsell, R., and Blundell, C · 2020
Closest in time.
What can neural networks reason about?
Xu, K., Li, J., Zhang, M., Du, S. S., Kawarabayashi, K., and Jegelka, S · 2020
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Yan, Y., Swersky, K., Koutra, D., Ranganathan, P., and Hashemi, M · 2020
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