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 1121–1130 of 3569 papers

TitleStatusHype
Hypernetworks build Implicit Neural Representations of SoundsCode1
Enhancing Modality-Agnostic Representations via Meta-Learning for Brain Tumor Segmentation—0
Memory-Based Meta-Learning on Non-Stationary DistributionsCode1
APAM: Adaptive Pre-training and Adaptive Meta Learning in Language Model for Noisy Labels and Long-tailed Learning—0
Meta-Learning Siamese Network for Few-Shot Text ClassificationCode1
Cross-Frequency Time Series Meta-Forecasting—0
Efficient Gradient Approximation Method for Constrained Bilevel Optimization—0
Learning to Optimize for Reinforcement LearningCode1
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning—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