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 2851–2900 of 3569 papers

TitleStatusHype
Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex ProgrammingCode0
Learning to Learn Words from Visual ScenesCode0
Learning to Modulate Random Weights: Neuromodulation-inspired Neural Networks For Efficient Continual LearningCode0
Learning to Multi-Task by Active SamplingCode0
Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for Fine-grained Emotion RecognitionCode0
Fast Efficient Hyperparameter Tuning for Policy GradientsCode0
Learning to learn ecosystems from limited data -- a meta-learning approachCode0
Provable Guarantees for Gradient-Based Meta-LearningCode0
Fast Adaptive Meta-Learning for Few-Shot Image GenerationCode0
Learning to Propagate for Graph Meta-LearningCode0
Learning to Propagate Labels: Transductive Propagation Network for Few-shot LearningCode0
Learning to Learn Cropping Models for Different Aspect Ratio RequirementsCode0
Learning to Rasterize DifferentiablyCode0
Learning to Learn By Self-CritiqueCode0
Far-HO: A Bilevel Programming Package for Hyperparameter Optimization and Meta-LearningCode0
Asynchronous Distributed Bilevel OptimizationCode0
Learning to Rectify for Robust Learning with Noisy LabelsCode0
Learning to reinforcement learnCode0
Provable Meta-Learning of Linear RepresentationsCode0
Learning to reinforcement learn for Neural Architecture SearchCode0
Fairness Warnings and Fair-MAML: Learning Fairly with Minimal DataCode0
Speaker Adaptive Training using Model Agnostic Meta-LearningCode0
Learning to learn by gradient descent by gradient descentCode0
On the Convergence Theory of Debiased Model-Agnostic Meta-Reinforcement LearningCode0
Analyzing the Effectiveness of Quantum Annealing with Meta-LearningCode0
Learning to Generate Noise for Multi-Attack RobustnessCode0
Learning to Forget for Meta-LearningCode0
Consistency of Compositional Generalization across Multiple LevelsCode0
Extreme Algorithm Selection With Dyadic Feature RepresentationCode0
ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement LearningCode0
Adaptive Mixing of Auxiliary Losses in Supervised LearningCode0
Learning to Few-Shot Learn Across Diverse Natural Language Classification TasksCode0
A Partially Supervised Reinforcement Learning Framework for Visual Active SearchCode0
Proxy Network for Few Shot LearningCode0
Pseudo-Labeling Based Practical Semi-Supervised Meta-Training for Few-Shot LearningCode0
Generalizable and Robust Spectral Method for Multi-view Representation LearningCode0
Concurrent Meta Reinforcement LearningCode0
Learning to Explore for Stochastic Gradient MCMCCode0
Learning to Evolve on Dynamic GraphsCode0
Learning Unknowns from Unknowns: Diversified Negative Prototypes Generator for Few-Shot Open-Set RecognitionCode0
Concept-free Causal Disentanglement with Variational Graph Auto-EncoderCode0
Writer adaptation for offline text recognition: An exploration of neural network-based methodsCode0
Learning vs Retrieval: The Role of In-Context Examples in Regression with LLMsCode0
Learning What and Where to TransferCode0
Learning to Discretize: Solving 1D Scalar Conservation Laws via Deep Reinforcement LearningCode0
Learning Where to Edit Vision TransformersCode0
Meta Temporal Point ProcessesCode0
Learning to Design RNACode0
Learning to Demodulate from Few Pilots via Offline and Online Meta-LearningCode0
Improving Few-Shot Learning through Multi-task Representation Learning TheoryCode0
Show:102550
← PrevPage 58 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