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 10261050 of 3569 papers

TitleStatusHype
Associative Alignment for Few-shot Image ClassificationCode0
Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot CoordinationCode0
Assessor-Guided Learning for Continual EnvironmentsCode0
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal PredictionCode0
Cross-Modal Generalization: Learning in Low Resource Modalities via Meta-AlignmentCode0
Learning advisor networks for noisy image classificationCode0
Learning an Explicit Hyperparameter Prediction Function Conditioned on TasksCode0
Learning Deep Morphological Networks with Neural Architecture SearchCode0
learn2learn: A Library for Meta-Learning ResearchCode0
Leaping Through Time with Gradient-based Adaptation for RecommendationCode0
Cross-domain Transfer of Valence Preferences via a Meta-optimization ApproachCode0
Cross-domain Multi-modal Few-shot Object Detection via Rich TextCode0
A Hierarchical Bayesian Model for Deep Few-Shot Meta LearningCode0
Adaptive Cascading Network for Continual Test-Time AdaptationCode0
Feature Extractor Stacking for Cross-domain Few-shot LearningCode0
A Simple Neural Attentive Meta-LearnerCode0
An Ensemble of Epoch-wise Empirical Bayes for Few-shot LearningCode0
Learning Generalized Zero-Shot Learners for Open-Domain Image GeolocalizationCode0
Cross-Domain Few-Shot Graph ClassificationCode0
A Greedy Approach to Adapting the Trace Parameter for Temporal Difference LearningCode0
Cross-Domain Continual Learning via CLAMPCode0
Latent-Optimized Adversarial Neural Transfer for Sarcasm DetectionCode0
Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic MaterialCode0
A Simple Approach to Adversarial Robustness in Few-shot Image ClassificationCode0
LabelCraft: Empowering Short Video Recommendations with Automated Label CraftingCode0
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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