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 2621–2630 of 3569 papers

TitleStatusHype
Darts: User-Friendly Modern Machine Learning for Time Series—0
Data-Efficient and Robust Task Selection for Meta-Learning—0
Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks—0
Data Efficient Direct Speech-to-Text Translation with Modality Agnostic Meta-Learning—0
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning—0
Dataset Meta-Learning from Kernel-Ridge Regression—0
Dataset Meta-Learning from Kernel Ridge-Regression—0
DAWSON: A Domain Adaptive Few Shot Generation Framework—0
Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning—0
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks—0
Show:102550
← PrevPage 263 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