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 3301–3350 of 3569 papers

TitleStatusHype
A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-LearningCode0
Black box meta-learning intrinsic rewards for sparse-reward environmentsCode0
Scrutinize What We Ignore: Reining In Task Representation Shift Of Context-Based Offline Meta Reinforcement LearningCode0
Adaptation-Agnostic Meta-TrainingCode0
Online Parameter-Free Learning of Multiple Low Variance TasksCode0
Deep Multimodal Fusion for Generalizable Person Re-identificationCode0
Unsupervised Representation Learning to Aid Semi-Supervised Meta LearningCode0
Guided evolutionary strategies: Augmenting random search with surrogate gradientsCode0
Online-Within-Online Meta-LearningCode0
BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity RepresentatioCode0
Meta-learning from Tasks with Heterogeneous Attribute SpacesCode0
Unsupervised Task Clustering for Multi-Task Reinforcement LearningCode0
Deep Learning Theory Review: An Optimal Control and Dynamical Systems PerspectiveCode0
A MIND for Reasoning: Meta-learning for In-context DeductionCode0
Task Augmentation by Rotating for Meta-LearningCode0
Meta-learning how to Share Credit among Macro-ActionsCode0
Deep Compressed SensingCode0
SeFNet: Bridging Tabular Datasets with Semantic Feature NetsCode0
Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text GenerationCode0
Decomposed Meta-Learning for Few-Shot Sequence LabelingCode0
On Provably Robust Meta-Bayesian OptimizationCode0
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic ChoicesCode0
Decoder Choice Network for Meta-LearningCode0
Meta-Learning Initializations for Image SegmentationCode0
Are LSTMs Good Few-Shot Learners?Code0
GSHOT: Few-shot Generative Modeling of Labeled GraphsCode0
On Taking Advantage of Opportunistic Meta-knowledge to Reduce Configuration Spaces for Automated Machine LearningCode0
Gradient Estimators for Implicit ModelsCode0
Been There, Done That: Meta-Learning with Episodic RecallCode0
On the adaptation of in-context learners for system identificationCode0
Adaptive Meta-learner via Gradient Similarity for Few-shot Text ClassificationCode0
Meta-Learning Integration in Hierarchical Reinforcement Learning for Advanced Task ComplexityCode0
Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta LearningCode0
BayesPCN: A Continually Learnable Predictive Coding Associative MemoryCode0
Gradient-Based Meta-Learning with Learned Layerwise Metric and SubspaceCode0
Self-Distillation with Meta Learning for Knowledge Graph CompletionCode0
A comparison of small sample methods for Handshape RecognitionCode0
Addressing Catastrophic Forgetting in Few-Shot ProblemsCode0
A Meta-Transfer Objective for Learning to Disentangle Causal MechanismsCode0
Deciphering Trajectory-Aided LLM Reasoning: An Optimization PerspectiveCode0
Bayesian Meta Sampling for Fast Uncertainty AdaptationCode0
Meta Architecture SearchCode0
Bayesian Meta-Learning Through Variational Gaussian ProcessesCode0
Uncertainty-Aware Meta-Learning for Multimodal Task DistributionsCode0
A meta-learning recommender system for hyperparameter tuning: predicting when tuning improves SVM classifiersCode0
Deceptive Fairness Attacks on Graphs via Meta LearningCode0
A Closer Look at the Training Strategy for Modern Meta-LearningCode0
Self-Supervised Generalisation with Meta Auxiliary LearningCode0
Meta-Learning of Structured Task Distributions in Humans and MachinesCode0
Task-Embedded Control Networks for Few-Shot Imitation LearningCode0
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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