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 1001–1050 of 3569 papers

TitleStatusHype
Dataset Distillation with Infinitely Wide Convolutional NetworksCode0
Dataset Distillation using Neural Feature RegressionCode0
Dataset2Vec: Learning Dataset Meta-FeaturesCode0
Adaptive Cross-Modal Few-Shot LearningCode0
Learning to Continually Learn Rapidly from Few and Noisy DataCode0
Learning to Customize Model Structures for Few-shot Dialogue Generation TasksCode0
AI-Driven Discovery of High Performance Polymer Electrodes for Next-Generation BatteriesCode0
A Stylometric Inquiry into Hyperpartisan and Fake NewsCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
Learning to Defer to a Population: A Meta-Learning ApproachCode0
Data-Driven Performance Guarantees for Classical and Learned OptimizersCode0
Data-driven Meta-set Based Fine-Grained Visual ClassificationCode0
Learning to adapt: a meta-learning approach for speaker adaptationCode0
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learningCode0
DAMSL: Domain Agnostic Meta Score-based LearningCode0
Structured Prediction for Conditional Meta-LearningCode0
Learning Task-Aware Energy Disaggregation: a Federated ApproachCode0
Learning New Tasks from a Few Examples with Soft-Label PrototypesCode0
Adaptive Conditional Quantile Neural ProcessesCode0
Learning Invariances for Policy GeneralizationCode0
Curriculum Meta-Learning for Few-shot ClassificationCode0
Learning Low-Dimensional Embeddings for Black-Box OptimizationCode0
Learning How to Demodulate from Few Pilots via Meta-LearningCode0
Learning One-Shot Imitation from Humans without HumansCode0
Learning Fast Adaptation with Meta Strategy OptimizationCode0
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
Show:102550
← PrevPage 21 of 72Next →
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