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Found 3 papers, 3 papers with code
CMVAE: Causal Meta VAE for Unsupervised Meta-Learning
Unsupervised meta-learning aims to learn the meta knowledge from unlabeled data and rapidly adapt to novel tasks.
GraftNet: Towards Domain Generalized Stereo Matching with a Broad-Spectrum and Task-Oriented Feature
Although supervised deep stereo matching networks have made impressive achievements, the poor generalization ability caused by the domain gap prevents them from being applied to real-life scenarios.
Transductive Few-Shot Classification on the Oblique Manifold
Few-shot learning (FSL) attempts to learn with limited data.
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