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Found 5 papers, 0 papers with code
Almost Surely Asymptotically Constant Graph Neural Networks
Our results apply to a broad class of random graph models, including sparse and dense variants of the Erd\H{o}s-R\'enyi model, the stochastic block model, and the Barab\'asi-Albert model.
Towards Unbiased Exploration in Partial Label Learning
We consider learning a probabilistic classifier from partially-labelled supervision (inputs denoted with multiple possibilities) using standard neural architectures with a softmax as the final layer.
Query Answering with Transitive and Linear-Ordered Data
We consider entailment problems involving powerful constraint languages such as frontier-guarded existential rules in which we impose additional semantic restrictions on a set of distinguished relations.
Reasoning about disclosure in data integration in the presence of source constraints
Data integration systems allow users to access data sitting in multiple sources by means of queries over a global schema, related to the sources via mappings.
Goal-Driven Query Answering for Existential Rules with Equality
We show empirically that our technique can significantly improve the performance of query answering, and that it can mean the difference between answering a query in a few seconds or not being able to process the query at all.
