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 261–270 of 3569 papers

TitleStatusHype
Improving Generalization in Meta-learning via Task AugmentationCode1
A Structured Dictionary Perspective on Implicit Neural RepresentationsCode1
A Simple Approach to Case-Based Reasoning in Knowledge BasesCode1
Domain Adaptive Few-Shot Open-Set LearningCode1
DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend ForecastingCode1
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled DataCode1
AReLU: Attention-based Rectified Linear UnitCode1
Discovering Temporally-Aware Reinforcement Learning AlgorithmsCode1
Are Deep Neural Networks SMARTer than Second Graders?Code1
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot LearningCode1
Show:102550
← PrevPage 27 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