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 1861–1870 of 3569 papers

TitleStatusHype
SB-MTL: Score-based Meta Transfer-Learning for Cross-Domain Few-Shot Learning—0
Scalable Meta-Learning via Mixed-Mode Differentiation—0
Scalable Meta-Learning with Gaussian Processes—0
Scaling Opponent Shaping to High Dimensional Games—0
Scarce Data Driven Deep Learning of Drones via Generalized Data Distribution Space—0
Scenario-Agnostic Zero-Trust Defense with Explainable Threshold Policy: A Meta-Learning Approach—0
Search-based Optimisation of LLM Learning Shots for Story Point Estimation—0
Searching for Efficient Multi-Scale Architectures for Dense Image Prediction—0
Seeded self-play for language learning—0
Seeker based Adaptive Guidance via Reinforcement Meta-Learning Applied to Asteroid Close Proximity Operations—0
Show:102550
← PrevPage 187 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