AdvDeepLearning_ResearchPaperSurvey

Research paper review

“Few-shot Graph Classification with Contrastive Loss and Meta-classifier”

what is a few-shot classification?

Few-shot classification aims to learn a classifier to recognize unseen classes during training with limited labeled examples.

Introduction:

“Few-shot Graph Classification with Contrastive Loss and Meta-classifier,” a paper by Chao Wei and Zhidong Deng, investigates the problem of few-shot graph classification. They presented a novel graph contrastive relation network (GCRNet) by introducing a practical yet straightforward graph meta-baseline with contrastive loss and meta-classifier, which achieved comparable performance for graph few-shot learning.

Paper Link: https://ieeexplore-ieee-org.libaccess.sjlibrary.org/stamp/stamp.jsp?tp=&arnumber=9892886&tag=1

Medium Article Link: https://medium.com/@rawatakanksha2020/a-birds-eye-view-of-few-shot-graph-classification-with-contrastive-loss-and-meta-classifier-e91cc05cdf63

Slide Share Link: https://www.slideshare.net/AkankshaRawat53/paperreview-fewshot-graph-classification-with-contrastive-loss-and-metaclassifier-by-chao-wei-zhidong-deng-2pptx

Youtube Video Link: https://youtu.be/Uv1taAFhStA

References:

https://ieeexplore-ieee-org.libaccess.sjlibrary.org/stamp/stamp.jsp?tp=&arnumber=9892886&tag=1

https://sites.google.com/view/a-closer-look-at-few-shot/?pli=1

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