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 1401–1450 of 3569 papers

TitleStatusHype
Decentralized Gossip-Based Stochastic Bilevel Optimization over Communication Networks—0
Improve Noise Tolerance of Robust Loss via Noise-Awareness—0
Continuous-Time Meta-Learning with Forward Mode Differentiation—0
Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity—0
A Survey on Knowledge Editing of Neural Networks—0
Improving both domain robustness and domain adaptability in machine translation—0
Generalized Cross-domain Multi-label Few-shot Learning for Chest X-rays—0
Generalization of Model-Agnostic Meta-Learning Algorithms: Recurring and Unseen Tasks—0
Learning Attentive Meta-Transfer—0
A Systematic Decade Review of Trip Route Planning with Travel Time Estimation based on User Preferences and Behavior—0
Generalization in Neural Networks: A Broad Survey—0
Learning a Meta-Solver for Syntax-Guided Program Synthesis—0
Generalizable speech deepfake detection via meta-learned LoRA—0
Improving Few-Shot Visual Classification with Unlabelled Examples—0
A General framework for PAC-Bayes Bounds for Meta-Learning—0
Improving Generalization via Meta-Learning on Hard Samples—0
Adapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling—0
Decoupled Pronunciation and Prosody Modeling in Meta-Learning-Based Multilingual Speech Synthesis—0
Decoupling Adaptation from Modeling with Meta-Optimizers for Meta Learning—0
Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation—0
When MAML Can Adapt Fast and How to Assist When It Cannot—0
Improving the Generalization of Meta-learning on Unseen Domains via Adversarial Shift—0
Improving the performance of weak supervision searches using transfer and meta-learning—0
Improving the Reliability for Confidence Estimation—0
Learning a Terrain- and Robot-Aware Dynamics Model for Autonomous Mobile Robot Navigation—0
Imputation of missing values in multi-view data—0
In-Context In-Context Learning with Transformer Neural Processes—0
In-Context Learning for Few-Shot Molecular Property Prediction—0
In-Context Learning for Gradient-Free Receiver Adaptation: Principles, Applications, and Theory—0
Deep Interactive Bayesian Reinforcement Learning via Meta-Learning—0
Generalizable Representation Learning for Mixture Domain Face Anti-Spoofing—0
In-context learning of evolving data streams with tabular foundational models—0
Generalizable Person Re-Identification by Domain-Invariant Mapping Network—0
Continuous Learning in a Hierarchical Multiscale Neural Network—0
Are encoders able to learn landmarkers for warm-starting of Hyperparameter Optimization?—0
Age and Power Minimization via Meta-Deep Reinforcement Learning in UAV Networks—0
Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment—0
Incremental Few-Shot Object Detection—0
Generalizable Neural Fields as Partially Observed Neural Processes—0
Incremental Meta-Learning via Indirect Discriminant Alignment—0
Meta-Learning Mean Functions for Gaussian Processes—0
Generalizable Heuristic Generation Through Large Language Models with Meta-Optimization—0
Indic Languages Automatic Speech Recognition using Meta-Learning Approach—0
Inductive Linear Probing for Few-shot Node Classification—0
Inexact-ADMM Based Federated Meta-Learning for Fast and Continual Edge Learning—0
Inferential Text Generation with Multiple Knowledge Sources and Meta-Learning—0
Generalizable Deep Learning Method for Suppressing Unseen and Multiple MRI Artifacts Using Meta-learning—0
Influential Prototypical Networks for Few Shot Learning: A Dermatological Case Study—0
Information-Aware Time Series Meta-Contrastive Learning—0
Continual Quality Estimation with Online Bayesian Meta-Learning—0
Show:102550
← PrevPage 29 of 72Next →
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