Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
-
Updated
Sep 22, 2017 - Python
Pytorch implementation of the paper "Optimization as a Model for Few-Shot Learning"
implementation of relationNet naive version
Tensorflow implementation of NIPS 2017 Paper "Prototypical Networks for Few-shot Learning"
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
Triplet Loss implementation of Deep Speaker
Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"
Code and dataset of AAAI2019 paper Hybrid Attention-Based Prototypical Networks for Noisy Few-Shot Relation Classification
Hierarchical Co-occurrence Network with Prototype Loss for Few-shot Learning (PyTorch)
Code containing implementation of prototypical networks paper with a few tweaks
A PyTorch implementation of OpenAI's REPTILE algorithm
Evaluation framework for different few-shot-learning algorithm
The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
Implementation for <Neural Similarity Learning> in NeurIPS'19.
Tools for generating mini-ImageNet dataset and processing batches
FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography
Source code for NeurIPS 2020 paper "Node Classification on Graphs with Few-Shot Novel Labels via Meta Transformed Network Embedding"
EMNLP-2020: Cross-lingual Spoken Language Understanding with Regularized Representation Alignment
Tools for generating tieredImageNet dataset and processing batches
Add a description, image, and links to the few-shot topic page so that developers can more easily learn about it.
To associate your repository with the few-shot topic, visit your repo's landing page and select "manage topics."