Prototypical Networks for Few-shot Learning
Use a distance metric in the loss to determine to which class does an object belongs to from a few examples.
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- 2026-10-10
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Matching Networks for One Shot Learning arxiv.org
Interesting way of doing one-shot learning with low-data by using an attention mechanism and a query to compare an image to other images for classification.
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Matching Networks for One Shot Learning arxiv.org
Classify a new example from a list of other examples (without definitive categories) and with low-data per classification task, but lots of data for lots of similar classification tasks - it seems better than siamese networks. To sum up: with Matching Networks, you can optimize…
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hopfield-networks github.com
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Clustering scikit-learn.org
Education › Papers > Convolutional Neural Networks: “Use a distance metric in the loss to determine to which class does an object belongs to from a few examples.”