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목록Set Transformer (2)
Research Notes
[Paper Review] Reciptor: An Effective Pretrained Model for Recipe Representation Learning
Title: Reciptor: An Effective Pretrained Model for Recipe Representation Learning Authors: Diya Li, Mohammed J. Zaki Summary a joint approach for learning effective pretrained recipe embeddings using both the ingredients and cooking instructions a novel set transformer-based joint model to learn recipe representations that preserve permutation-invariance Framework Tags data: Model Validation에 사용..
[Paper Review] Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
Title: Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks Authors: Juho Lee, Yoonho Lee, Jungtaek Kim, Adam R. Kosiorek, Seungjin Choi, Yee Whye Teh 0. Abstract 다양한 ML tasks는 set의 순서에 의존하지 않는 *permutation invariant한 특성을 반영하지 못함 기존 모델의 이러한 한계로, Attention-based neural network model인 Set Transformer를 제안함 Set Transformer는 input set 내 요소들의 interaction을 반영할 수 있도록 설계..