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 1441–1450 of 3569 papers

TitleStatusHype
Meta-Learning Mean Functions for Gaussian Processes—0
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization—0
Indic Languages Automatic Speech Recognition using Meta-Learning Approach—0
Inductive Linear Probing for Few-shot Node Classification—0
Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning—0
Inferential Text Generation with Multiple Knowledge Sources and Meta-Learning—0
Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning—0
Influential Prototypical Networks for Few Shot Learning: A Dermatological Case Study—0
Information-Aware Time Series Meta-Contrastive Learning—0
Continual Quality Estimation with Online Bayesian Meta-Learning—0
Show:102550
← PrevPage 145 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