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 3221–3230 of 3569 papers

TitleStatusHype
Diversity with Cooperation: Ensemble Methods for Few-Shot ClassificationCode0
T2-Only Prostate Cancer Prediction by Meta-Learning from Bi-Parametric MR ImagingCode0
Robust Meta-learning with Sampling Noise and Label Noise via Eigen-ReptileCode0
High-order structure preserving graph neural network for few-shot learningCode0
META-Learning Eligibility Traces for More Sample Efficient Temporal Difference LearningCode0
Robust Meta-Representation Learning via Global Label Inference and ClassificationCode0
Robust Molecular Property Prediction via Densifying Scarce Labeled DataCode0
Robustness of Meta Matrix Factorization Against Strict Privacy ConstraintsCode0
Meta-learning enhanced next POI recommendation by leveraging check-ins from auxiliary citiesCode0
Hierarchically Structured Meta-learningCode0
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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