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Found 3 papers, 3 papers with code
Transferable Candidate Proposal with Bounded Uncertainty
To tackle this issue, we introduce a new experimental design, coined as Candidate Proposal, to find transferable data candidates from which active learning algorithms choose the informative subset.
Neural Processes with Stochastic Attention: Paying more attention to the context dataset
Neural processes (NPs) aim to stochastically complete unseen data points based on a given context dataset.
Ranked #1 on
Multi-agent Reinforcement Learning
on SMAC-Exp
Meta-learning Amidst Heterogeneity and Ambiguity
Meta-learning aims to learn a model that can handle multiple tasks generated from an unknown but shared distribution.
