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 851–900 of 3569 papers

TitleStatusHype
Meta-Meta Classification for One-Shot LearningCode0
Balanced Direction from Multifarious Choices: Arithmetic Meta-Learning for Domain GeneralizationCode0
Learning to Generate Noise for Multi-Attack RobustnessCode0
Learning to Forget for Meta-LearningCode0
ALPaCA vs. GP-based Prior Learning: A Comparison between two Bayesian Meta-Learning AlgorithmsCode0
MetaGL: Evaluation-Free Selection of Graph Learning Models via Meta-LearningCode0
Differentiable plasticity: training plastic neural networks with backpropagationCode0
Adaptive Gradient-Based Meta-Learning MethodsCode0
Learning to Explore for Stochastic Gradient MCMCCode0
Learning to Evolve on Dynamic GraphsCode0
Learning to Design RNACode0
DiCE: The Infinitely Differentiable Monte Carlo EstimatorCode0
DiCE: The Infinitely Differentiable Monte-Carlo EstimatorCode0
Adaptive Mixing of Auxiliary Losses in Supervised LearningCode0
Learning to Demodulate from Few Pilots via Offline and Online Meta-LearningCode0
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement LearningCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-TrainingCode0
A Unified Meta-Learning Framework for Dynamic Transfer LearningCode0
Meta-Gradient Reinforcement LearningCode0
Detecting Sockpuppetry on Wikipedia Using Meta-LearningCode0
Learning to Continually Learn Rapidly from Few and Noisy DataCode0
Designing Time-Series Models With Hypernetworks & Adversarial PortfoliosCode0
Learning to Balance: Bayesian Meta-Learning for Imbalanced and Out-of-distribution TasksCode0
MetaKernel: Learning Variational Random Features with Limited LabelsCode0
Delving into Sample Loss Curve to Embrace Noisy and Imbalanced DataCode0
Learning to Customize Model Structures for Few-shot Dialogue Generation TasksCode0
Learning to adapt: a meta-learning approach for speaker adaptationCode0
Meta Architecture SearchCode0
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian OptimizationCode0
A Closer Look at the Training Strategy for Modern Meta-LearningCode0
Bayesian Meta Sampling for Fast Uncertainty AdaptationCode0
AugFL: Augmenting Federated Learning with Pretrained ModelsCode0
Effective Structured Prompting by Meta-Learning and Representative VerbalizerCode0
Deep Transfer Learning Based Downlink Channel Prediction for FDD Massive MIMO SystemsCode0
Learning to acquire novel cognitive tasks with evolution, plasticity and meta-meta-learningCode0
Deep Task-Based Analog-to-Digital ConversionCode0
Adaptive Fine-Grained Sketch-Based Image RetrievalCode0
Learning One-Shot Imitation from Humans without HumansCode0
Learning Task-Aware Energy Disaggregation: a Federated ApproachCode0
Learning to Defer to a Population: A Meta-Learning ApproachCode0
Learning to learn by gradient descent by gradient descentCode0
Meta-Learning Bidirectional Update RulesCode0
Learning Invariances for Policy GeneralizationCode0
Algorithm Selection on a Meta LevelCode0
Learning Low-Dimensional Embeddings for Black-Box OptimizationCode0
Learning How to Demodulate from Few Pilots via Meta-LearningCode0
Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal PredictionCode0
Adaptive Posterior Learning: few-shot learning with a surprise-based memory moduleCode0
Learning Generalized Zero-Shot Learners for Open-Domain Image GeolocalizationCode0
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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