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On Sufficient and Necessary Conditions in Bounded CTL: A Forgetting Approach
To address such a scenario in a principled way, we introduce a forgetting-based approach in CTL and show that it can be used to compute SNC and WSC of a property under a given model and over a given signature.
Quantum and Translation Embedding for Knowledge Graph Completion
The insight of this work enlightens the notion of dense feature model design for KGC which is a new alternative to Deep Neural networks (DNN) in this task or even a better choice.
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