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 2501–2525 of 3569 papers

TitleStatusHype
Boosting Model Resilience via Implicit Adversarial Data Augmentation—0
Boosting Natural Language Generation from Instructions with Meta-Learning—0
BP-DeepONet: A new method for cuffless blood pressure estimation using the physcis-informed DeepONet—0
Brain-inspired global-local learning incorporated with neuromorphic computing—0
Breaking Immutable: Information-Coupled Prototype Elaboration for Few-Shot Object Detection—0
Bridging or Breaking: Impact of Intergroup Interactions on Religious Polarization—0
Bridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study—0
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning—0
Bridging the Reality Gap of Reinforcement Learning based Traffic Signal Control using Domain Randomization and Meta Learning—0
Budget-aware Few-shot Learning via Graph Convolutional Network—0
CAD: Co-Adapting Discriminative Features for Improved Few-Shot Classification—0
CAFENet: Class-Agnostic Few-Shot Edge Detection Network—0
Calibrating Wireless AI via Meta-Learned Context-Dependent Conformal Prediction—0
Camera-Invariant Meta-Learning Network for Single-Camera-Training Person Re-identification—0
CAML: Fast Context Adaptation via Meta-Learning—0
Can Gradient Descent Simulate Prompting?—0
Can we achieve robustness from data alone?—0
CATCH: Context-based Meta Reinforcement Learning for Transferrable Architecture Search—0
Category-Agnostic 6D Pose Estimation with Conditional Neural Processes—0
Category-level Meta-learned NeRF Priors for Efficient Object Mapping—0
Causality-Driven One-Shot Learning for Prostate Cancer Grading from MRI—0
CAZSL: Zero-Shot Regression for Pushing Models by Generalizing Through Context—0
CCML: Curriculum and Contrastive Learning Enhanced Meta-Learner for Personalized Spatial Trajectory Prediction—0
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process—0
Cellular neuromodulation in artificial 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