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 91–100 of 3569 papers

TitleStatusHype
Component-Based Fairness in Face Attribute Classification with Bayesian Network-informed Meta LearningCode0
Learning Low-Dimensional Embeddings for Black-Box OptimizationCode0
CICADA: Cross-Domain Interpretable Coding for Anomaly Detection and Adaptation in Multivariate Time Series—0
Learning to Learn with Quantum Optimization via Quantum Neural Networks—0
Scalable Meta-Learning via Mixed-Mode Differentiation—0
Task-Agnostic Semantic Communications Relying on Information Bottleneck and Federated Meta-Learning—0
Meta knowledge assisted Evolutionary Neural Architecture Search—0
Toward Evaluative Thinking: Meta Policy Optimization with Evolving Reward ModelsCode0
Meta-learning based Selective Fixed-filter Active Noise Control System with ResNet Classifier—0
CAMeL: Cross-modality Adaptive Meta-Learning for Text-based Person RetrievalCode1
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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