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 921–930 of 3569 papers

TitleStatusHype
Efficient Model Compression Techniques with FishLeg—0
Reinforcement learning to learn quantum states for Heisenberg scaling accuracyCode0
Towards Cross-Lingual Audio Abuse Detection in Low-Resource Settings with Few-Shot LearningCode0
Learn to Unlearn: Meta-Learning-Based Knowledge Graph Embedding Unlearning—0
Meta-learning Loss Functions of Parametric Partial Differential Equations Using Physics-Informed Neural Networks—0
QUOTA: Quantifying Objects with Text-to-Image Models for Any Domain—0
On the ERM Principle in Meta-Learning—0
MetaGraphLoc: A Graph-based Meta-learning Scheme for Indoor Localization via Sensor Fusion—0
Material synthesis through simulations guided by machine learning: a position paper—0
MetaCropFollow: Few-Shot Adaptation with Meta-Learning for Under-Canopy Navigation—0
Show:102550
← PrevPage 93 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