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 14011425 of 3569 papers

TitleStatusHype
Constrained Few-Shot Learning: Human-Like Low Sample Complexity Learning and Non-Episodic Text Classification0
Hierarchical Attention Network for Few-Shot Object Detection via Meta-Contrastive LearningCode1
ROLAND: Graph Learning Framework for Dynamic GraphsCode3
Visual Localization via Few-Shot Scene Region ClassificationCode1
GEDI: A Graph-based End-to-end Data Imputation Framework0
Learning to Infer Counterfactuals: Meta-Learning for Estimating Multiple Imbalanced Treatment Effects0
Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation0
Intelligent MIMO Detection Using Meta Learning0
On Taking Advantage of Opportunistic Meta-knowledge to Reduce Configuration Spaces for Automated Machine LearningCode0
A Game-Theoretic Perspective of Generalization in Reinforcement Learning0
Learning to Generalize with Object-centric Agents in the Open World Survival Game CrafterCode1
SA-NET.v2: Real-time vehicle detection from oblique UAV images with use of uncertainty estimation in deep meta-learning0
Transformers as Meta-Learners for Implicit Neural RepresentationsCode1
Meta-learning from Learning Curves Challenge: Lessons learned from the First Round and Design of the Second Round0
Homomorphisms Between Transfer, Multi-Task, and Meta-Learning Systems0
Improving Meta-Learning Generalization with Activation-Based Early-StoppingCode0
Augmentation Learning for Semi-Supervised Classification0
Centroids Matching: an efficient Continual Learning approach operating in the embedding spaceCode0
Stochastic Deep Networks with Linear Competing Units for Model-Agnostic Meta-LearningCode0
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence0
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation ExploitationCode2
Sampling Attacks on Meta Reinforcement Learning: A Minimax Formulation and Complexity AnalysisCode0
A Survey of Learning on Small Data: Generalization, Optimization, and Challenge0
Meta-Learning based Degradation Representation for Blind Super-ResolutionCode1
Towards Sleep Scoring Generalization Through Self-Supervised Meta-Learning0
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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