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Neural Logic Networks
[article]
2019
arXiv
pre-print
Recent years have witnessed the great success of deep neural networks in many research areas. The fundamental idea behind the design of most neural networks is to learn similarity patterns from data for prediction and inference, which lacks the ability of logical reasoning. However, the concrete ability of logical reasoning is critical to many theoretical and practical problems. In this paper, we propose Neural Logic Network (NLN), which is a dynamic neural architecture that builds the
arXiv:1910.08629v1
fatcat:634xfrpabrhshcl5k2irjo5tq4