Bayesian Model-Agnostic Meta-Learning The proposed method combines scalable gradient-based meta-learning with nonparametric variational inference in a principled probabilistic framework. During fast ... T Kim,J Yoon,O Dia,... 被引量: 33发表: 2018年 A probabilistic framework for memory-based reasonin...
Meta-Transfer Learning for Few-Shot Learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, Long Beach, CA, USA, 16–20 June 2019; pp. 403–412. [Google Scholar] Finn, C.; Abbeel, P.; Levine, S. Model-Agnostic Meta-Learning for Fast Adaptation ...
4.3. The Model Specification Language To specify a model in a language that is as close as possible to the mathematical representation of a model, we employ Julia’s [31] powerful meta-programming functionality to create our own syntax. By creating our own syntax using the @model macro, we...