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 2151–2200 of 3569 papers

TitleStatusHype
Noether Networks: Meta-Learning Useful Conserved Quantities—0
A Multi-Strategy based Pre-Training Method for Cold-Start Recommendation—0
Self-supervised Graph Learning for Occasional Group Recommendation—0
Fast Data-Driven Adaptation of Radar Detection via Meta-Learning—0
Meta Arcade: A Configurable Environment Suite for Meta-Learning—0
Automatic Unsupervised Outlier Model Selection—0
Learning to Learn Dense Gaussian Processes for Few-Shot Learning—0
Fast Training Method for Stochastic Compositional Optimization Problems—0
Meta-Learning via Learning with Distributed Memory—0
Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation—0
Effective Meta-Regularization by Kernelized Proximal Regularization—0
On the Practical Consistency of Meta-Reinforcement Learning Algorithms—0
Generative vs. Discriminative: Rethinking The Meta-Continual LearningCode0
Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery—0
Variational Continual Bayesian Meta-Learning—0
MAMRL: Exploiting Multi-agent Meta Reinforcement Learning in WAN Traffic Engineering—0
Leveraging The Topological Consistencies of Learning in Deep Neural Networks—0
Confounder Identification-free Causal Visual Feature Learning—0
A Close Look at Few-shot Real Image Super-resolution from the Distortion Relation Perspective—0
Joint inference and input optimization in equilibrium networksCode0
Meta Mask Correction for Nuclei Segmentation in Histopathological Image—0
Exploration of Dark Chemical Genomics Space via Portal Learning: Applied to Targeting the Undruggable Genome and COVID-19 Anti-Infective Polypharmacology—0
Sharing to learn and learning to share; Fitting together Meta-Learning, Multi-Task Learning, and Transfer Learning: A meta review—0
Meta-learning richer priors for VAEs—0
Reinforcement Learning for Few-Shot Text Generation AdaptationCode0
Generating meta-learning tasks to evolve parametric loss for classification learning—0
Visual Goal-Directed Meta-Learning with Contextual Planning Networks—0
Meta Learning for Code Summarization—0
DAML-ST5: Low Resource Style Transfer via Domain Adaptive Meta Learning—0
DAML: Chinese Named Entity Recognition with a fusion method of data-augmentation and meta-learning—0
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis—0
Unsupervised Domain Adaptation for Event Detection via Meta Self-Paced Learning—0
MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningCode0
A Self-Adaptive Learning Rate and Curriculum Learning Based Framework for Few-Shot Text Classification—0
Meta-learning via Language Model In-context Tuning—0
Persian Natural Language Inference: A Meta-learning approach—0
MetaPrompting: Learning to Learn Better Prompts—0
ST-SQL: Semi-Supervised Self-Training for Text-to-SQL via Column Specificity Meta-LearningCode0
A Meta-Learning Approach for Few-Shot (Dis)Agreement Identification in Online Discussions—0
Meta-Adapter: Parameter Efficient Few-Shot Learning through Meta-Learning—0
Online Meta Adaptation for Variable-Rate Learned Image Compression—0
Learn to Adapt for Generalized Zero-Shot Text Classification—0
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations—0
Metric-based multimodal meta-learning for human movement identification via footstep recognition—0
ModelLight: Model-Based Meta-Reinforcement Learning for Traffic Signal Control—0
Meta-Voice: Fast few-shot style transfer for expressive voice cloning using meta learning—0
Learning to Evolve on Dynamic GraphsCode0
Learning Online for Unified Segmentation and Tracking Models—0
Cross-lingual Adaption Model-Agnostic Meta-Learning for Natural Language Understanding—0
OSSEM: one-shot speaker adaptive speech enhancement using meta learning—0
Show:102550
← PrevPage 44 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