mabirck/adaptative-dropout-pytorch
Pytorch implementation of Adaptative Dropout a.ka Standout.
This project helps machine learning researchers or practitioners explore a specific neural network regularization technique called Adaptive Dropout (also known as Standout). It takes a neural network model built with PyTorch and applies this dropout method during training. The output is a trained model that aims to generalize better by reducing overfitting, though the current implementation notes indicate it may not perfectly replicate published performance benchmarks.
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Use this if you are a machine learning researcher or deep learning practitioner experimenting with regularization techniques in PyTorch and specifically want to test or understand Adaptive Dropout.
Not ideal if you are looking for an out-of-the-box solution to immediately improve your model's performance without extensive experimentation, or if you require guaranteed state-of-the-art results without further tuning.
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Python
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MIT
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Last pushed
Feb 22, 2018
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