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 1661–1670 of 3569 papers

TitleStatusHype
Ground-Truth Free Meta-Learning for Deep Compressive Sampling—0
Global Perception Based Autoregressive Neural Processes—0
MetaMix: Towards Corruption-Robust Continual Learning With Temporally Self-Adaptive Data Transformation—0
s-Adaptive Decoupled Prototype for Few-Shot Object Detection—0
An Erudite Fine-Grained Visual Classification Model—0
Learn TAROT with MENTOR: A Meta-Learned Self-Supervised Approach for Trajectory Prediction—0
Eliminating Meta Optimization Through Self-Referential Meta Learning—0
Wormhole MAML: Meta-Learning in Glued Parameter Space—0
On Implicit Bias in Overparameterized Bilevel Optimization—0
Meta-Learning for Color-to-Infrared Cross-Modal Style Transfer—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