Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
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Updated
Jan 28, 2021 - Python
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Repository for few-shot learning machine learning projects
Implementation of Siamese Neural Networks for One-shot Image Recognition
Implementation of One Shot Learning using Convolutional Siamese Networks on Omniglot Dataset
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Multi-task learning for image classification implemented in PyTorch.
Implementation of Prototypical Networks for Few-shot Learning in TensorFlow 2.0
Solutions to tasks in over 700 programming languages
Implementation of Siamese-Networks for One Shot Learning in TensorFlow 2.0
Cluttered Omniglot dataset and models
This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.
一些数据集处理相关的 API
One Shot Learning Implementation
a deep recurrent model for exchangeable data
A ready to go implementation of the "Siamese Neural Networks for One-shot Image Recognition" paper in PyTorch on Google Colab with training and testing on the Omniglot/custom datasets.
Example of one shot learning and few shot learning with omniglot dataset.
Implementation of "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
Prototypical Networks for the task of few-shot image classification on Omniglot and mini-ImageNet.
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