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Ken Forbus

4 accepted papers

2023

Sketch Recognition via Part-based Hierarchical Analogical Learning

IJCAI 2023poster

Sketch recognition has been studied for decades, but it is far from solved. Drawing styles are highly variable across people and adapting to idiosyncratic visual expressions requires data-efficient learning. Explainability also matters, so that users can see why a system got confused about something…

Cited by 4SourcePDFScholar
2020

Mapping natural-language problems to formal-language solutions using structured neural representations

ICML 2020poster

Generating formal-language programs represented by relational tuples, such as Lisp programs or mathematical operations, to solve problems stated in natural language is a challenging task because it requires explicitly capturing discrete symbolic structural information implicit in the input. However,…

Cited by 37SourcePDFScholar