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

Showing 426450 of 3569 papers

TitleStatusHype
Meta-DMoE: Adapting to Domain Shift by Meta-Distillation from Mixture-of-ExpertsCode1
BaMBNet: A Blur-aware Multi-branch Network for Defocus DeblurringCode1
MetaF2N: Blind Image Super-Resolution by Learning Efficient Model Adaptation from FacesCode1
MetaFBP: Learning to Learn High-Order Predictor for Personalized Facial Beauty PredictionCode1
Meta-FDMixup: Cross-Domain Few-Shot Learning Guided by Labeled Target DataCode1
Adaptive Multi-Teacher Knowledge Distillation with Meta-LearningCode1
Meta-HAR: Federated Representation Learning for Human Activity RecognitionCode1
MetaHTR: Towards Writer-Adaptive Handwritten Text RecognitionCode1
Meta Internal LearningCode1
Meta-Learned Models of CognitionCode1
Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text ClassificationCode1
Meta-learning an Intermediate Representation for Few-shot Block-wise Prediction of Landslide SusceptibilityCode1
ContrastNet: A Contrastive Learning Framework for Few-Shot Text ClassificationCode1
Meta-Learning Biologically Plausible Plasticity Rules with Random Feedback PathwaysCode1
Meta-learning curiosity algorithmsCode1
Bayesian Model-Agnostic Meta-LearningCode1
Meta-learning Extractors for Music Source SeparationCode1
BERT Learns to Teach: Knowledge Distillation with Meta LearningCode1
Meta-Learning for Semi-Supervised Few-Shot ClassificationCode1
Meta-learning framework with applications to zero-shot time-series forecastingCode1
Meta-Learning Initializations for Low-Resource Drug DiscoveryCode1
Contrastive Meta Learning with Behavior Multiplicity for RecommendationCode1
Meta-Learning Sparse Implicit Neural RepresentationsCode1
Control-oriented meta-learningCode1
Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real WorldCode1
Show:102550
← PrevPage 18 of 143Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8Unverified
2MZMeta-train success rate97.6Unverified
3MAMLMeta-test success rate36Unverified
4RL^2Meta-test success rate10Unverified
5DnCMeta-test success rate5.4Unverified
6PEARLMeta-test success rate0Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60Unverified
2Multi-task multi-head SACAverage Success Rate35.85Unverified
3DisCorAverage Success Rate26Unverified
4NDPAverage Success Rate11Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5Unverified
2MZMeta-test success rate (zero-shot)17.7Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75Unverified