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 911–920 of 3569 papers

TitleStatusHype
LogitMat : Zeroshot Learning Algorithm for Recommender Systems without Transfer Learning or Pretrained Models—0
Meta Federated Reinforcement Learning for Distributed Resource Allocation—0
Personalized Federated Learning via Amortized Bayesian Meta-Learning—0
Meta-Learning Adversarial Bandit Algorithms—0
First-Explore, then Exploit: Meta-Learning to Solve Hard Exploration-Exploitation Trade-OffsCode1
All in One: Multi-task Prompting for Graph Neural Networks—0
Improving Language Plasticity via Pretraining with Active ForgettingCode1
Model-Assisted Probabilistic Safe Adaptive Control With Meta-Bayesian Learning—0
OpenClinicalAI: An Open and Dynamic Model for Alzheimer's Disease Diagnosis—0
Graph Sampling-based Meta-Learning for Molecular Property PredictionCode1
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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