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 1726–1750 of 3569 papers

TitleStatusHype
Fast Adaptive Federated Bilevel Optimization—0
Meta-Learning for Unsupervised Outlier Detection with Optimal Transport—0
A Meta-GNN approach to personalized seizure detection and classification—0
Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach—0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Data-Efficient Cross-Lingual Transfer with Language-Specific Subnetworks—0
A new benchmark for group distribution shifts in hand grasp regression for object manipulation. Can meta-learning raise the bar?Code0
Few-Shot Classification of Skin Lesions from Dermoscopic Images by Meta-Learning Representative EmbeddingsCode0
RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR PredictionCode0
SEMPAI: a Self-Enhancing Multi-Photon Artificial Intelligence for prior-informed assessment of muscle function and pathology—0
Meta-Learning Initializations for Interactive Medical Image Registration—0
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking—0
Which is the best model for my data?—0
Imputation of missing values in multi-view data—0
Multi-Environment based Meta-Learning with CSI Fingerprints for Radio Based Positioning—0
Auxiliary task discovery through generate-and-test—0
Learning to Augment via Implicit Differentiation for Domain Generalization—0
UTILIZING FEDERATED LEARNING AND META LEARNING FOR FEW-SHOT LEARNING ON EDGE DEVICES—0
Leveraging Open Data and Task Augmentation to Automated Behavioral Coding of Psychotherapy Conversations in Low-Resource Scenarios—0
A Meta-Learning Based Gradient Descent Algorithm for MU-MIMO Beamforming—0
MARS: Meta-Learning as Score Matching in the Function SpaceCode0
Self-Configuring nnU-Nets Detect Clouds in Satellite Images—0
Federated Learning and Meta Learning: Approaches, Applications, and Directions—0
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks—0
MetaEMS: A Meta Reinforcement Learning-based Control Framework for Building Energy Management System—0
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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