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 2591–2600 of 3569 papers

TitleStatusHype
Meta-GCN: A Dynamically Weighted Loss Minimization Method for Dealing with the Data Imbalance in Graph Neural Networks—0
Meta Generative Attack on Person Reidentification—0
Meta Generative Flow Networks with Personalization for Task-Specific Adaptation—0
MetaGMT: Improving Actionable Interpretability of Graph Multilinear Networks via Meta-Learning Filtration—0
Meta Gradient Boosting Neural Networks—0
MetaGraphLoc: A Graph-based Meta-learning Scheme for Indoor Localization via Sensor Fusion—0
Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation—0
MetaHistoSeg: A Python Framework for Meta Learning in Histopathology Image Segmentation—0
Meta-Inductive Node Classification across Graphs—0
MetaInfoNet: Learning Task-Guided Information for Sample Reweighting—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