Few-Shot Learning with Graph Neural Networks
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| Authors | Victor Garcia, Joan Bruna |
| Journal/Conference Name | 6th International Conference on Learning Representations, ICLR 2018 - Conference Track Proceedings |
| Paper Category | Artificial Intelligence |
| Paper Abstract | We propose to study the problem of few-shot learning with the prism of inference on a partially observed graphical model, constructed from a collection of input images whose label can be either observed or not. By assimilating generic message-passing inference algorithms with their neural-network counterparts, we define a graph neural network architecture that generalizes several of the recently proposed few-shot learning models. Besides providing improved numerical performance, our framework is easily extended to variants of few-shot learning, such as semi-supervised or active learning, demonstrating the ability of graph-based models to operate well on 'relational' tasks. |
| Date of publication | 2017 |
| Code Programming Language | Multiple |
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