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 641–650 of 3569 papers

TitleStatusHype
Meta Adversarial Training against Universal PatchesCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
MetaAudio: A Few-Shot Audio Classification BenchmarkCode1
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth ImagesCode1
HELP: Hardware-Adaptive Efficient Latency Prediction for NAS via Meta-LearningCode1
Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration ErrorCode1
Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few ExamplesCode1
Covariate Distribution Aware Meta-learningCode1
MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta LearningCode1
MetaVIM: Meta Variationally Intrinsic Motivated Reinforcement Learning for Decentralized Traffic Signal ControlCode1
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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