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 18011825 of 3569 papers

TitleStatusHype
Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated LearningCode0
Defending against Poisoning Backdoor Attacks on Federated Meta-learning0
An Investigation of the Bias-Variance Tradeoff in Meta-GradientsCode0
On the Convergence Theory of Meta Reinforcement Learning with Personalized Policies0
Adaptive Local-Component-aware Graph Convolutional Network for One-shot Skeleton-based Action Recognition0
MAC: A Meta-Learning Approach for Feature Learning and Recombination0
Meta-Reinforcement Learning for Adaptive Control of Second Order Systems0
Meta-Adapters: Parameter Efficient Few-shot Fine-tuning through Meta-LearningCode0
MetaDIP: Accelerating Deep Image Prior with Meta Learning0
SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction0
FRANS: Automatic Feature Extraction for Time Series Forecasting0
Classical Sequence Match is a Competitive Few-Shot One-Class LearnerCode0
Meta-RegGNN: Predicting Verbal and Full-Scale Intelligence Scores using Graph Neural Networks and Meta-LearningCode0
Decoupled Pronunciation and Prosody Modeling in Meta-Learning-Based Multilingual Speech Synthesis0
Federated Meta-Learning for Traffic Steering in O-RAN0
Designing Biological Sequences via Meta-Reinforcement Learning and Bayesian Optimization0
Learning domain-specific causal discovery from time series0
Online Continual Learning via the Meta-learning Update with Multi-scale Knowledge Distillation and Data Augmentation0
Style Variable and Irrelevant Learning for Generalizable Person Re-identificationCode0
Adaptive Meta-learner via Gradient Similarity for Few-shot Text ClassificationCode0
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath0
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition0
A Novel Semi-supervised Meta Learning Method for Subject-transfer Brain-computer Interface0
Scalable Adversarial Online Continual LearningCode0
Generalization in Neural Networks: A Broad Survey0
Show:102550
← PrevPage 73 of 143Next →

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