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 861870 of 3569 papers

TitleStatusHype
Generalizable Decision Boundaries: Dualistic Meta-Learning for Open Set Domain GeneralizationCode1
META-SELD: Meta-Learning for Fast Adaptation to the new environment in Sound Event Localization and Detection0
Embracing assay heterogeneity with neural processes for markedly improved bioactivity predictions0
Is Meta-Learning the Right Approach for the Cold-Start Problem in Recommender Systems?0
An Adaptive Approach for Probabilistic Wind Power Forecasting Based on Meta-Learning0
Dual Meta-Learning with Longitudinally Generalized Regularization for One-Shot Brain Tissue Segmentation Across the Human LifespanCode0
Privacy-preserving Few-shot Traffic Detection against Advanced Persistent Threats via Federated Meta LearningCode1
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation ProcessingCode0
Bayesian Meta-Learning on Control Barrier Functions with Data from On-Board Sensors0
Cross-heterogeneity Graph Few-shot Learning0
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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