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 791–800 of 3569 papers

Title	Date	Tasks	Status	Hype
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms	Oct 19, 2023	Meta-LearningMulti-Task Learning	CodeCode Available	0
Group Preference Optimization: Few-Shot Alignment of Large Language Models	Oct 17, 2023	Few-Shot LearningMeta-Learning	CodeCode Available	1
Context-Aware Meta-Learning	Oct 17, 2023	Few-Shot Image ClassificationIn-Context Learning	CodeCode Available	1
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot Classification	Oct 16, 2023	Data AugmentationMeta-Learning	CodeCode Available	1
BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity Representatio	Oct 15, 2023	Drug DiscoveryMeta-Learning	CodeCode Available	0
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents	Oct 15, 2023	In-Context LearningIn-Context Reinforcement Learning	CodeCode Available	1
Dynamic Link Prediction for New Nodes in Temporal Graph Networks	Oct 15, 2023	Dynamic Link PredictionLink Prediction	—Unverified	0
A Partially Supervised Reinforcement Learning Framework for Visual Active Search	Oct 15, 2023	Deep Reinforcement LearningMeta-Learning	CodeCode Available	0
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks	Oct 14, 2023	Meta-Learning	—Unverified	0
Subspace Adaptation Prior for Few-Shot Learning	Oct 13, 2023	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	0

Show:10 25 50

← PrevPage 80 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