Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
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Updated
Sep 19, 2021 - Jupyter Notebook
Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
Implementation of Prototypical Networks for Few Shot Learning (https://arxiv.org/abs/1703.05175) in Pytorch
Few-shot classification in Named Entity Recognition Task
A few shot learning repository for bearing fault diagnosis.
Few-Shot Keyword Spotting
Implementation of Prototypical Networks for Few-shot Learning in TensorFlow 2.0
A novel method for few shot learning
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.
(Using) Prototypical Networks as a Fine Grained Classifier
Deepest Season 6 Meta-Learning study papers plus alpha
Official code of the CVPR 2022 paper "Proto2Proto: Can you recognize the car, the way I do?"
PyTorch implementation for "ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback" (https://arxiv.org/abs/2107.14035).
Code containing implementation of prototypical networks paper with a few tweaks
Official repository for the paper "ProtoASNet: Dynamic Prototypes for Inherently Interpretable and Uncertainty-Aware Aortic Stenosis Classification in Echocardiography" in MICCAI 2023 Conference
Prototypical Networks for the task of few-shot image classification on Omniglot and mini-ImageNet.
Official Implementation of "SPN: Stable Prototypical Network for Few-Shot Learning-Based Hyperspectral Image Classification" (GRSL22)
GUI based tool to train and develop Few Shot Classification ML model.
The code for "Efficient-PrototypicalNet with self knowledge distillation for few-shot learning"
We explore different techniques to perform few-shot-classification of fashion images.
Meta Learning implementations via PyTorch (without any other frameworks)
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