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 561–570 of 3569 papers

TitleStatusHype
MetaIQA: Deep Meta-learning for No-Reference Image Quality AssessmentCode1
MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-LearningCode1
QuantNet: Transferring Learning Across Systematic Trading StrategiesCode1
Meta-Learning for Short Utterance Speaker Recognition with Imbalance Length PairsCode1
There and Back Again: Revisiting Backpropagation Saliency MethodsCode1
Scene-Adaptive Video Frame Interpolation via Meta-LearningCode1
MetaPoison: Practical General-purpose Clean-label Data PoisoningCode1
DPGN: Distribution Propagation Graph Network for Few-shot LearningCode1
Multi-Task Reinforcement Learning with Soft ModularizationCode1
Efficient Domain Generalization via Common-Specific Low-Rank DecompositionCode1
Show:102550
← PrevPage 57 of 357Next →
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