SOTAVerified|Agents Browse Leaderboard About

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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 361–370 of 3569 papers

Title	Date	Tasks	Status	Hype	Score
Learning Neural Causal Models from Unknown Interventions	Oct 2, 2019	Meta-Learning	CodeCode Available	1	5
Attention Guided Cosine Margin For Overcoming Class-Imbalance in Few-Shot Road Object Detection	Nov 12, 2021	Few-Shot Object DetectionMeta-Learning	CodeCode Available	1	5
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels	Oct 11, 2019	Bayesian InferenceDomain Adaptation	CodeCode Available	1	5
Fast Online Adaptation in Robotics through Meta-Learning Embeddings of Simulated Priors	Mar 10, 2020	Meta-LearningModel-based Reinforcement Learning	CodeCode Available	1	5
Attentive Weights Generation for Few Shot Learning via Information Maximization	Jun 1, 2020	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning	Mar 30, 2018	continuous-controlContinuous Control	CodeCode Available	1	5
Delving Deep Into Many-to-Many Attention for Few-Shot Video Object Segmentation	Jun 19, 2021	Meta-LearningSemantic Segmentation	CodeCode Available	1	5
Federated Reconstruction: Partially Local Federated Learning	Feb 5, 2021	Collaborative FilteringFederated Learning	CodeCode Available	1	5
Learning to Continually Learn	Feb 21, 2020	Continual LearningLifelong learning	CodeCode Available	1	5
A Broader Study of Cross-Domain Few-Shot Learning	Dec 16, 2019	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1	5

Show:10 25 50

← PrevPage 37 of 357Next →

All datasets ML10 MT50 ML45 OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	MZ+Recon	Meta-train success rate	97.8	—	Unverified
2	MZ	Meta-train success rate	97.6	—	Unverified
3	MAML	Meta-test success rate	36	—	Unverified
4	RL^2	Meta-test success rate	10	—	Unverified
5	DnC	Meta-test success rate	5.4	—	Unverified
6	PEARL	Meta-test success rate	0	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SoftModule	Average Success Rate	60	—	Unverified
2	Multi-task multi-head SAC	Average Success Rate	35.85	—	Unverified
3	DisCor	Average Success Rate	26	—	Unverified
4	NDP	Average Success Rate	11	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MZ+Recon	Meta-test success rate (zero-shot)	18.5	—	Unverified
2	MZ	Meta-test success rate (zero-shot)	17.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Metadrop	% Test Accuracy	95.75	—	Unverified