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 2321–2330 of 3569 papers

TitleStatusHype
Introducing Symmetries to Black Box Meta Reinforcement Learning—0
MetaMedSeg: Volumetric Meta-learning for Few-Shot Organ SegmentationCode0
Semi-Supervised Few-Shot Intent Classification and Slot Filling—0
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning—0
Few-Shot Object Detection by Attending to Per-Sample-Prototype—0
Sign-MAML: Efficient Model-Agnostic Meta-Learning by SignSGDCode0
Partner-Assisted Learning for Few-Shot Image Classification—0
Should We Be Pre-training? An Argument for End-task Aware Training as an AlternativeCode0
Few-shot Quality-Diversity OptimizationCode0
One-Class Meta-Learning: Towards Generalizable Few-Shot Open-Set Classification—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