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 201250 of 3569 papers

TitleStatusHype
Few-shot Classification via Adaptive AttentionCode1
Few-Shot Class-Incremental Learning by Sampling Multi-Phase TasksCode1
A Physics-Informed Meta-Learning Framework for the Continuous Solution of Parametric PDEs on Arbitrary GeometriesCode1
Few-shot Image Classification: Just Use a Library of Pre-trained Feature Extractors and a Simple ClassifierCode1
A Meta-Learning Approach for Graph Representation Learning in Multi-Task SettingsCode1
An Enhanced Span-based Decomposition Method for Few-Shot Sequence LabelingCode1
Camera Distortion-aware 3D Human Pose Estimation in Video with Optimization-based Meta-LearningCode1
A Meta-Learning Approach for Training Explainable Graph Neural NetworksCode1
Few-Shot Named Entity Recognition: A Comprehensive StudyCode1
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
Few-Shot Object Detection via Variational Feature AggregationCode1
Few-Shot One-Class Classification via Meta-LearningCode1
Few-shot Relational Reasoning via Connection Subgraph PretrainingCode1
Few-shot Relation Extraction via Bayesian Meta-learning on Relation GraphsCode1
Adaptive Multi-Teacher Knowledge Distillation with Meta-LearningCode1
Few-shot Text Classification with Distributional SignaturesCode1
Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the WildCode1
Few-shot Visual Relationship Co-localizationCode1
Continued Pretraining for Better Zero- and Few-Shot PromptabilityCode1
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image ClassificationCode1
FLEX: Unifying Evaluation for Few-Shot NLPCode1
Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed AdaptationCode1
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-LearningCode1
Adversarial Feature Augmentation for Cross-domain Few-shot ClassificationCode1
Generalising via Meta-Examples for Continual Learning in the WildCode1
Generalizable Black-Box Adversarial Attack with Meta LearningCode1
Blind Super-Resolution via Meta-learning and Markov Chain Monte Carlo SimulationCode1
Generalizable No-Reference Image Quality Assessment via Deep Meta-learningCode1
Generating and Weighting Semantically Consistent Sample Pairs for Ultrasound Contrastive LearningCode1
Generative Meta-Learning Robust Quality-Diversity PortfolioCode1
BOME! Bilevel Optimization Made Easy: A Simple First-Order ApproachCode1
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot LearningCode1
A Brain Graph Foundation Model: Pre-Training and Prompt-Tuning for Any Atlas and DisorderCode1
GPT-PINN: Generative Pre-Trained Physics-Informed Neural Networks toward non-intrusive Meta-learning of parametric PDEsCode1
Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue GenerationCode1
Graph Few-shot Class-incremental LearningCode1
Graph Meta Network for Multi-Behavior RecommendationCode1
Graph Prototypical Networks for Few-shot Learning on Attributed NetworksCode1
AReLU: Attention-based Rectified Linear UnitCode1
GS-Phong: Meta-Learned 3D Gaussians for Relightable Novel View SynthesisCode1
HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement LearningCode1
Harnessing Meta-Learning for Improving Full-Frame Video StabilizationCode1
How Sensitive are Meta-Learners to Dataset Imbalance?Code1
Amortized Probabilistic Conditioning for Optimization, Simulation and InferenceCode1
Adaptive Subspaces for Few-Shot LearningCode1
How to train your MAMLCode1
A contrastive rule for meta-learningCode1
Hypernetwork approach to Bayesian MAMLCode1
Adaptive Transfer Learning on Graph Neural NetworksCode1
Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning ApproachCode1
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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