Repository for few-shot learning machine learning projects
-
Updated
Nov 25, 2019 - Python
Repository for few-shot learning machine learning projects
Code for the NeurIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Implementation of Siamese Neural Networks for One-shot Image Recognition
This repo provides pytorch code which replicates the results of the Matching Networks for One Shot Learning paper on the Omniglot and MiniImageNet dataset
Solutions to tasks in over 700 programming languages
Implementation of One Shot Learning using Convolutional Siamese Networks on Omniglot 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
Cluttered Omniglot dataset and models
一些数据集处理相关的 API
Implementation of Siamese-Networks for One Shot Learning in TensorFlow 2.0
One Shot Learning Implementation
a deep recurrent model for exchangeable data
Implementation of Matching Networks for One Shot Learning in TensorFlow 2.0
Example of one shot learning and few shot learning with omniglot dataset.
This repository implements the paper, Model-Agnostic Meta-Leanring for Fast Adaptation of Deep Networks.
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.
Add a description, image, and links to the omniglot topic page so that developers can more easily learn about it.
To associate your repository with the omniglot topic, visit your repo's landing page and select "manage topics."