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 11311140 of 3569 papers

TitleStatusHype
It HAS to be Subjective: Human Annotator Simulation via Zero-shot Density EstimationCode0
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?Code0
Investigating Large Language Models for Complex Word Identification in Multilingual and Multidomain SetupsCode0
An Unsupervised Cross-Modal Hashing Method Robust to Noisy Training Image-Text Correspondences in Remote SensingCode0
Inverse Learning with Extremely Sparse Feedback for RecommendationCode0
Joint inference and input optimization in equilibrium networksCode0
Knowledge-enhanced Relation Graph and Task Sampling for Few-shot Molecular Property PredictionCode0
INR-Arch: A Dataflow Architecture and Compiler for Arbitrary-Order Gradient Computations in Implicit Neural Representation ProcessingCode0
Comparing the Efficacy of Fine-Tuning and Meta-Learning for Few-Shot Policy ImitationCode0
Compare More Nuanced:Pairwise Alignment Bilinear Network For Few-shot Fine-grained LearningCode0
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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