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Andreea Deac

2 accepted papers

2021

How to transfer algorithmic reasoning knowledge to learn new algorithms?

NeurIPS 2021poster

Learning to execute algorithms is a fundamental problem that has been widely studied. Prior work (Veličković et al., 2019) has shown that to enable systematic generalisation on graph algorithms it is critical to have access to the intermediate steps of the program/algorithm. In many reasoning tasks,…

Cited by 32SourcePDFScholar
2021

Neural Algorithmic Reasoners are Implicit Planners

NeurIPS 2021spotlight

Implicit planning has emerged as an elegant technique for combining learned models of the world with end-to-end model-free reinforcement learning. We study the class of implicit planners inspired by value iteration, an algorithm that is guaranteed to yield perfect policies in fully-specified tabular…

Cited by 25SourcePDFScholar