Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
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Updated
Feb 9, 2018 - Jupyter Notebook
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Literature on learning from small amount of labeled data
Deep Learning for Computer Vision 2018 Spring
This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)
improving generalization via scalable neighborhood component analysis
Lowshot learning with Tensorflow
PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Zero-Shot Learning part)
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
Few-shot classification in Named Entity Recognition Task
Development of few-shot learning tool for a variety of image classes, utitilizing features extracted from ConvNets.
Codes for low-shot-shrink-hallucinate paper imported from official repository and with added helper functions
Curated List of Few shot and One shot Learning Papers and resources
Meta-learning by applying MAML to an inner variational auto-encoder to automatically learn generative models with few examples
Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
Few-Shot Relation Extraction with AllenNLP
Awesome papers in few-shot learning/one-shot learning.
Matching Networks for one-shot learning in tensorflow (NIPS'16)
Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
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