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 191–200 of 3569 papers

TitleStatusHype
Efficient Domain Generalization via Common-Specific Low-Rank DecompositionCode1
Efficient Graph Deep Learning in TensorFlow with tf_geometricCode1
End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-LearningCode1
Bayesian Model-Agnostic Meta-LearningCode1
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive AgentsCode1
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter OptimizationCode1
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-LearningCode1
Exploiting Domain-Specific Features to Enhance Domain GeneralizationCode1
Exploring Effective Factors for Improving Visual In-Context LearningCode1
BOML: A Modularized Bilevel Optimization Library in Python for Meta LearningCode1
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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