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

One Shot Learning Implementation

Implementation of Siamese-Networks for One Shot Learning in TensorFlow 2.0

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.

Implementation of Siamese Networks using PyTorch

Implementation of Few-shot Binary Image Classification using Contrastive Learning-based Approach in PyTorch

Implementation for paper "BATMANN: A Binarized-All-Through Memory-Augmented Neural Network for Efficient In-Memory Computing"