maml pytorch

We have hosted the application maml pytorch in order to run this application in our online workstations with Wine or directly.

Quick description about maml pytorch:

MAML-Pytorch is a PyTorch implementation of Model-Agnostic Meta-Learning for supervised learning experiments. It focuses on reproducing and exploring the MAML approach for few-shot learning research. The repository supports MiniImagenet and Omniglot, two common benchmark datasets for meta-learning experiments. It includes separate training scripts, dataset loaders, learner components, and meta-learning logic. The project also notes that MAML can be difficult to train and presents the implementation as a practical starting point for research. Overall, it is useful for students and researchers who want to study fast adaptation, few-shot classification, and gradient-based meta-learning in PyTorch.

Features:

• PyTorch implementation of Model-Agnostic Meta-Learning
• Support for MiniImagenet and Omniglot experiments
• Few-shot supervised learning research focus
• Meta learner and basic learner implementation
• Training scripts for benchmark datasets
• MIT licensed research starting point

Programming Language: Python.
Categories: