SOTAVerified

Meta-Learning

Meta-learning is a methodology considered with "learning to learn" machine learning algorithms.

( Image credit: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3341–3350 of 3569 papers

TitleStatusHype
MetaCloth: Learning Unseen Tasks of Dense Fashion Landmark Detection from a Few Samples—0
MetaComp: Learning to Adapt for Online Depth Completion—0
Meta Compositional Referring Expression Segmentation—0
MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning—0
Meta-Continual Learning of Neural Fields—0
MetaCon: Unified Predictive Segments System with Trillion Concept Meta-Learning—0
Meta-CoTGAN: A Meta Cooperative Training Paradigm for Improving Adversarial Text Generation—0
Meta-CQG: A Meta-Learning Framework for Complex Question Generation over Knowledge Graph—0
Meta-CQG: A Meta-Learning Framework for Complex Question Generation over Knowledge Bases—0
MetaCropFollow: Few-Shot Adaptation with Meta-Learning for Under-Canopy Navigation—0
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All datasetsML10MT50ML45OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8—Unverified
2MZMeta-train success rate97.6—Unverified
3MAMLMeta-test success rate36—Unverified
4RL^2Meta-test success rate10—Unverified
5DnCMeta-test success rate5.4—Unverified
6PEARLMeta-test success rate0—Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60—Unverified
2Multi-task multi-head SACAverage Success Rate35.85—Unverified
3DisCorAverage Success Rate26—Unverified
4NDPAverage Success Rate11—Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5—Unverified
2MZMeta-test success rate (zero-shot)17.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75—Unverified