Few-shot classification in Named Entity Recognition Task
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Updated
Dec 18, 2018 - Python
Few-shot classification in Named Entity Recognition Task
(Using) Prototypical Networks as a Fine Grained Classifier
Code containing implementation of prototypical networks paper with a few tweaks
A novel method for few shot learning
Deepest Season 6 Meta-Learning study papers plus alpha
Few-Shot Keyword Spotting
Prototypical Networks on Omniglot Dataset for Few-Shot Classification
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
Prototypical Networks for the task of few-shot image classification on Omniglot and mini-ImageNet.
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
Official code of the CVPR 2022 paper "Proto2Proto: Can you recognize the car, the way I do?"
We explore different techniques to perform few-shot-classification of fashion images.
This repo contains the implementation of some new papers on some advanced topics of machine learning e.g. meta-learning, reinforcement-learning, meta-reinforcement-learning, continual-learning and etc.
PyTorch implementation for "ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback" (https://arxiv.org/abs/2107.14035).
A streamlit web app that allows you to train Few Shot image classification models
GUI based tool to train and develop Few Shot Classification ML model.
Official Implementation of "SPN: Stable Prototypical Network for Few-Shot Learning-Based Hyperspectral Image Classification" (GRSL22)
A study on the interpretability of the concepts learned by Prototypical Part Networks (ProtoPNets) on the CUB200-2011 and CelebAMask datasets.
Prototypical Networks for Information Extraction in Visual Documents. Weights can be found at https://drive.google.com/file/d/1Zrp7QaZIf0H_FFRx_LhB0uZTqDUSis2H/view?usp=sharing.
The code for "Efficient-PrototypicalNet with self knowledge distillation for few-shot learning"
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