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Awesome-META+ dataset
The dataset used in the paper is a collection of meta-learning frameworks, including MAML, Prototypical Network, and others. -
Alchemy: A structured task distribution for meta-reinforcement learning
The Alchemy benchmark is a meta-learning environment rich enough to contain interesting abstractions, yet simple enough to make ne-grained analysis tractable. -
Multiple-confounded-Mujoco-Envs
The dataset used in the paper is a collection of environments with multiple confounders, including mass, length, damping, and a crippled leg. The dataset is used to evaluate the... -
Eigen-Reptile
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Mini-Imagenet and CIFAR-FS datasets for few-shot learning tasks. -
Meta-Meta Classification for One-Shot Learning
A new approach to meta-learning, called meta-meta classification, to learning in small-data settings. -
RotoGBML: Towards out-of-distribution generalization for gradient-based meta-...
RotoGBML: Towards out-of-distribution generalization for gradient-based meta-learning. -
Meta-dataset
A dataset of datasets for learning to learn from few examples. -
Meta-GraphSHS Dataset
This dataset is used to evaluate the performance of the proposed Meta-GraphSHS model for discovering structural hole spanners in diverse networks.
