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20212023
most citedFeature-Based Interpretable Reinforcement Learning based on State-Transition Models

5 citations · 11 across the 7 of their papers we have counts for

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cs.LG2022

Interpretable Few-shot Learning with Online Attribute Selection

Mohammad Reza Zarei, Majid Komeili

Few-shot learning (FSL) presents a challenging learning problem in which only a few samples are available for each class. Decision interpretation is more important in few-shot clas…

cs.LG2022

Interpretable Concept-based Prototypical Networks for Few-Shot Learning

Mohammad Reza Zarei, Majid Komeili

Few-shot learning aims at recognizing new instances from classes with limited samples. This challenging task is usually alleviated by performing meta-learning on similar tasks. How…