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
Collection for Few-shot Learning
Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
A python ZSL system which makes it easy to run Zero-Shot Learning on new datasets, by giving it features and attributes. Used for the paper "Zero-Shot Learning Based Approach For Medieval Word Recognition Using Deep-Learned Features", published in ICFHR2018.
Deepest Season 6 Meta-Learning study papers plus alpha
Meta Transfer Learning for Few Shot Semantic Segmentation using U-Net
One Shot Learning with Siamese Neural Networks + Triplet Siamese Neural Networks on Dark Web Images
Papers on meta-learning
A Signature Validation and Mandate Verification System by using Siamese Networks and One-Shot Learning.
Using one shot learning to classify paintings
An Application with interacts with the database using NLP and Langchain
Autocorrelation Sequence Prediction Model Based On Reference Function Transformation: Taking Epidemic Prediction As An Example
In this repository I list some course projects I did during my undergraduate at the School of Data Science, Fudan University.
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