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 3151–3200 of 3569 papers

TitleStatusHype
Effective Few-Shot Named Entity Linking by Meta-LearningCode0
Adaptive Prior Selection for Repertoire-based Online Adaptation in RoboticsCode0
Revisiting Unsupervised Meta-Learning via the Characteristics of Few-Shot TasksCode0
Natural Language to Structured Query Generation via Meta-LearningCode0
Revisit Multimodal Meta-Learning through the Lens of Multi-Task LearningCode0
Imitation Learning from Suboptimal Demonstrations via Meta-Learning An Action RankerCode0
Reward Design for Reinforcement Learning AgentsCode0
Meta-Learners for Few-Shot Weakly-Supervised Medical Image SegmentationCode0
Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video RecommendationCode0
Rewarded meta-pruning: Meta Learning with Rewards for Channel PruningCode0
Towards Enabling Meta-Learning from Target ModelsCode0
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian OptimizationCode0
Meta-Learning a Cross-lingual Manifold for Semantic ParsingCode0
Bootstrapped Meta-LearningCode0
An Efficient Memory Module for Graph Few-Shot Class-Incremental LearningCode0
Adaptive Posterior Learning: few-shot learning with a surprise-based memory moduleCode0
Neural Complexity MeasuresCode0
Imbalanced Regression Pipeline RecommendationCode0
Neural Context Flows for Meta-Learning of Dynamical SystemsCode0
Meta-learning algorithms for Few-Shot Computer VisionCode0
Meta-learning Amidst Heterogeneity and AmbiguityCode0
Meta-learning and Data Augmentation for Stress Testing Forecasting ModelsCode0
Dynamic Loss For Robust LearningCode0
Iceberg: Enhancing HLS Modeling with Synthetic DataCode0
Dynamic Kernel Selection for Improved Generalization and Memory Efficiency in Meta-learningCode0
Meta-Learning and Self-Supervised Pretraining for Real World Image TranslationCode0
Dual Meta-Learning with Longitudinally Generalized Regularization for One-Shot Brain Tissue Segmentation Across the Human LifespanCode0
Meta-Learning an Evolvable Developmental EncodingCode0
Dual-level Mixup for Graph Few-shot Learning with Fewer TasksCode0
Neuronal diversity can improve machine learning for physics and beyondCode0
Hyperparameter Optimization as a Service on INFN CloudCode0
Neural Networks for Threshold Dynamics ReconstructionCode0
Dual Attention Networks for Few-Shot Fine-Grained RecognitionCode0
Neural Routing in Meta LearningCode0
Towards Adaptive Meta-Gradient Adversarial Examples for Visual TrackingCode0
HyperMAN: Hypergraph-enhanced Meta-learning Adaptive Network for Next POI RecommendationCode0
Robust and Differentially Private Mean EstimationCode0
A Simple Approach to Adversarial Robustness in Few-shot Image ClassificationCode0
DRILL: Dynamic Representations for Imbalanced Lifelong LearningCode0
Meta-learning autoencoders for few-shot predictionCode0
Neuromodulated Meta-LearningCode0
Meta-Learning-Based Adaptive Stability Certificates for Dynamical SystemsCode0
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task LearningCode0
HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model CompressionCode0
How to Learn and Represent Abstractions: An Investigation using Symbolic AlchemyCode0
Towards An Efficient and Effective En Route Travel Time Estimation FrameworkCode0
DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse TasksCode0
How Neural Processes Improve Graph Link PredictionCode0
Adversarially Robust Few-Shot Learning: A Meta-Learning ApproachCode0
Double Equivariance for Inductive Link Prediction for Both New Nodes and New Relation TypesCode0
Show:102550
← PrevPage 64 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