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 601625 of 3569 papers

TitleStatusHype
Context-Aware Meta-LearningCode1
Meta-Learning for Semi-Supervised Few-Shot ClassificationCode1
Empirical Bayes Transductive Meta-Learning with Synthetic GradientsCode1
Meta-Learning Initializations for Low-Resource Drug DiscoveryCode1
ARCADe: A Rapid Continual Anomaly DetectorCode1
End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-LearningCode1
Learning to Detect Noisy Labels Using Model-Based FeaturesCode1
EvoGrad: Efficient Gradient-Based Meta-Learning and Hyperparameter OptimizationCode1
Adapting to Distribution Shift by Visual Domain Prompt GenerationCode1
Meta-Learning Sparse Implicit Neural RepresentationsCode1
On the Convergence Theory for Hessian-Free Bilevel AlgorithmsCode1
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot LearningCode1
Evading Forensic Classifiers with Attribute-Conditioned Adversarial FacesCode1
Meta-Learning to Compositionally GeneralizeCode1
Are Deep Neural Networks SMARTer than Second Graders?Code1
Continued Pretraining for Better Zero- and Few-Shot PromptabilityCode1
Expanding the Deployment Envelope of Behavior Prediction via Adaptive Meta-LearningCode1
Evolving Reinforcement Learning AlgorithmsCode1
Meta-learning with differentiable closed-form solversCode1
Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real WorldCode1
AReLU: Attention-based Rectified Linear UnitCode1
Exploiting Domain-Specific Features to Enhance Domain GeneralizationCode1
Exploration in Approximate Hyper-State Space for Meta Reinforcement LearningCode1
Exploring Effective Factors for Improving Visual In-Context LearningCode1
Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-LearningCode1
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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