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 626650 of 3569 papers

TitleStatusHype
Contrastive Meta-Learning for Partially Observable Few-Shot LearningCode1
Contrastive Meta Learning with Behavior Multiplicity for RecommendationCode1
Meta Adversarial Training against Universal PatchesCode1
ContrastNet: A Contrastive Learning Framework for Few-Shot Text ClassificationCode1
Control-oriented meta-learningCode1
A General Descent Aggregation Framework for Gradient-based Bi-level OptimizationCode1
Fast Adaptation to Super-Resolution Networks via Meta-LearningCode1
ArtFID: Quantitative Evaluation of Neural Style TransferCode1
Fast and Efficient Local Search for Genetic Programming Based Loss Function LearningCode1
Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated PriorsCode1
Meta Self-Learning for Multi-Source Domain Adaptation: A BenchmarkCode1
Faster Meta Update Strategy for Noise-Robust Deep LearningCode1
Simulating Unknown Target Models for Query-Efficient Black-box AttacksCode1
2021 BEETL Competition: Advancing Transfer Learning for Subject Independence & Heterogenous EEG Data SetsCode1
Few-shot Object Detection via Feature ReweightingCode1
Meta-Learning and Knowledge Discovery based Physics-Informed Neural Network for Remaining Useful Life PredictionCode1
Copolymer Informatics with Multi-Task Deep Neural NetworksCode1
Meta-Transfer Learning through Hard TasksCode1
MetaWeather: Few-Shot Weather-Degraded Image RestorationCode1
Few-shot Classification via Adaptive AttentionCode1
MetaXL: Meta Representation Transformation for Low-resource Cross-lingual LearningCode1
Few Shot Dialogue State Tracking using Meta-learningCode1
Covariate Distribution Aware Meta-learningCode1
Few-shot Decoding of Brain Activation MapsCode1
Personalized Federated Learning with Moreau EnvelopesCode1
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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