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 2191–2200 of 3569 papers

TitleStatusHype
Online Meta Adaptation for Variable-Rate Learned Image Compression—0
Learn to Adapt for Generalized Zero-Shot Text Classification—0
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations—0
Metric-based multimodal meta-learning for human movement identification via footstep recognition—0
ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control—0
Meta-Voice: Fast few-shot style transfer for expressive voice cloning using meta learning—0
Learning to Evolve on Dynamic GraphsCode0
Learning Online for Unified Segmentation and Tracking Models—0
Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding—0
OSSEM: one-shot speaker adaptive speech enhancement using meta learning—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