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 251–275 of 3569 papers

TitleStatusHype
Task-Specific Gradient Adaptation for Few-Shot One-Class Classification—0
M2I2: Learning Efficient Multi-Agent Communication via Masked State Modeling and Intention Inference—0
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded SmoothnessCode0
Transformer-Based Contrastive Meta-Learning For Low-Resource Generalizable Activity Recognition—0
Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action RankerCode0
Meta-Learning-Based Delayless Subband Adaptive Filter using Complex Self-Attention for Active Noise Control—0
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIsCode1
Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-LearningCode1
Automatic Self-supervised Learning for Social Recommendations—0
Mitigating Label Noise using Prompt-Based Hyperbolic Meta-Learning in Open-Set Domain GeneralizationCode0
Learning to Adapt to Low-Resource Paraphrase Generation—0
A Meta-Learning Approach to Bayesian Causal DiscoveryCode0
MetaRuleGPT: Recursive Numerical Reasoning of Language Models Trained with Simple Rules—0
Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion RecognitionCode0
Consistency of Compositional Generalization across Multiple LevelsCode0
TSEML: A task-specific embedding-based method for few-shot classification of cancer molecular subtypesCode0
Reservoir Computing for Fast, Simplified Reinforcement Learning on Memory Tasks—0
Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling—0
Generalizable Representation Learning for fMRI-based Neurological Disorder IdentificationCode0
LeARN: Learnable and Adaptive Representations for Nonlinear Dynamics in System Identification—0
Memory-Reduced Meta-Learning with Guaranteed Convergence—0
Meta Curvature-Aware Minimization for Domain Generalization—0
ViSymRe: Vision-guided Multimodal Symbolic Regression—0
Label-template based Few-Shot Text Classification with Contrastive Learning—0
Three-in-One: Robust Enhanced Universal Transferable Anti-Facial Retrieval in Online Social Networks—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