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 32013225 of 3569 papers

TitleStatusHype
Learning To Learn by Jointly Optimizing Neural Architecture and Weights0
Learning to Learn Dense Gaussian Processes for Few-Shot Learning0
Learning to Learn End-to-End Goal-Oriented Dialog From Related Dialog Tasks0
Learning to Learn for Few-shot Continual Active Learning0
Learning to Learn Group Alignment: A Self-Tuning Credo Framework with Multiagent Teams0
Learning to Learn in a Semi-Supervised Fashion0
Learning to Learn: Meta-Critic Networks for Sample Efficient Learning0
Learning to Learn Morphological Inflection for Resource-Poor Languages0
Learning to Learn Neural Networks0
Learning-to-learn non-convex piecewise-Lipschitz functions0
Learning-to-Learn Personalised Human Activity Recognition Models0
Learning to Learn Semantic Factors in Heterogeneous Image Classification0
Learning-to-Learn the Wave Angle Estimation0
Learning to Learn to be Right for the Right Reasons0
Learning to learn to communicate0
Learning to Learn Transferable Generative Attack for Person Re-Identification0
Learning to Learn Unlearned Feature for Brain Tumor Segmentation0
Learning to Learn Weight Generation via Local Consistency Diffusion0
Learning to Learn with Conditional Class Dependencies0
Learning to Learn with Feedback and Local Plasticity0
Learning to Learn with Indispensable Connections0
Learning to Learn with Quantum Optimization via Quantum Neural Networks0
Learning to Learn with Variational Information Bottleneck for Domain Generalization0
Learning to Navigate the Web0
Learning to Optimise General TSP Instances0
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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