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Jun, 2023
ProtoDiff: 任务引导扩散学习原型网络
ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion
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Yingjun Du, Zehao Xiao, Shengcai Liao, Cees Snoek
TL;DR
ProtoDiff是一种新框架,利用任务指导扩散模型逐步生成原型以提供有效的类别表示,从而解决了少样本学习挑战中确定原型的不确定性问题,并在领域内、领域间和少任务少样本分类上实现了新的最优性能。
Abstract
prototype-based meta-learning
has emerged as a powerful technique for addressing
few-shot learning
challenges. However, estimating a deterministic prototype using a simple average function from a limited number o
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