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 1071–1080 of 3569 papers

TitleStatusHype
CoMeta: Enhancing Meta Embeddings with Collaborative Information in Cold-start Problem of Recommendation—0
Few-Shot Classification of Autism Spectrum Disorder using Site-Agnostic Meta-Learning and Brain MRI—0
MetaTroll: Few-shot Detection of State-Sponsored Trolls with Transformer AdaptersCode0
Meta-learning approaches for few-shot learning: A survey of recent advances—0
Transformation-Invariant Network for Few-Shot Object Detection in Remote Sensing Images—0
Learning Distortion Invariant Representation for Image Restoration from A Causality PerspectiveCode1
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning—0
MetaUE: Model-based Meta-learning for Underwater Image EnhancementCode0
Gradient-Regulated Meta-Prompt Learning for Generalizable Vision-Language Models—0
Anomaly Detection with Ensemble of Encoder and Decoder—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