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 1476–1500 of 3569 papers

TitleStatusHype
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization—0
Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning—0
Introducing Symmetries to Black Box Meta Reinforcement Learning—0
Continual Quality Estimation with Online Bayesian Meta-Learning—0
Invariant Meta Learning for Out-of-Distribution Generalization—0
Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning—0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition—0
Learning to Actively Learn: A Robust Approach—0
Deep Unrolled Meta-Learning for Multi-Coil and Multi-Modality MRI with Adaptive Optimization—0
Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks—0
Investigating Relative Performance of Transfer and Meta Learning—0
Learning to Adapt to Low-Resource Paraphrase Generation—0
Continual learning under domain transfer with sparse synaptic bursting—0
GeneraLight: Improving Environment Generalization of Traffic Signal Control via Meta Reinforcement Learning—0
Is Fast Adaptation All You Need?—0
Continual Few-Shot Learning with Adversarial Class Storage—0
A Recursively Recurrent Neural Network (R2N2) Architecture for Learning Iterative Algorithms—0
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing—0
Is Pre-training Truly Better Than Meta-Learning?—0
Is Support Set Diversity Necessary for Meta-Learning?—0
Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?—0
GEDI: A Graph-based End-to-end Data Imputation Framework—0
Investigating Active Learning and Meta-Learning for Iterative Peptide Design—0
AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All—0
A real-time battle situation intelligent awareness system based on Meta-learning & RNN—0
Show:102550
← PrevPage 60 of 143Next →
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