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Found 3 papers, 2 papers with code
A Neural Model for Regular Grammar Induction
Grammatical inference is a classical problem in computational learning theory and a topic of wider influence in natural language processing.
Periodic Extrapolative Generalisation in Neural Networks
The learning of the simplest possible computational pattern -- periodicity -- is an open problem in the research of strong generalisation in neural networks.
FACT: Learning Governing Abstractions Behind Integer Sequences
Integer sequences are of central importance to the modeling of concepts admitting complete finitary descriptions.
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