https://github.com/raphael-baena/Local-Mixup

scripts, notebooks and dataset to run experiments on Local-Mixup
https://github.com/raphael-baena/Local-Mixup

Last synced: 3 months ago
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scripts, notebooks and dataset to run experiments on Local-Mixup

• Host: GitHub
• URL: https://github.com/raphael-baena/Local-Mixup
• Owner: raphael-baena
• License: gpl-2.0
• Created: 2022-07-27T12:24:46.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-27T12:38:53.000Z (over 2 years ago)
• Last Synced: 2024-05-12T22:44:10.402Z (6 months ago)
• Language: Jupyter Notebook
• Size: 49.8 KB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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• Awesome-Mixup - [Code

README

        
# Local-Mixup

This repo contains the code (notebooks, scripts) for Local Mixup, as presented in our paper "Preventing Manifold Intrusion with Locality: Local Mixup" (https://arxiv.org/abs/2201.04368).

We also provide the dataset of the two coiling spirals used in our paper. Note that this dataset can also be generated by the user with different values of noise. 

## Requirements and Installation:

1. A Pytorch installation https://pytorch.org

2. Python version 3.8.1 (lower versions might not work)

3. (optional) CIFAR10 dataset,CIAFAR100 dataset, SVHN, Fashion MNIST from https://pytorch.org/vision/stable/datasets.html.

## Experiments

### Low dimension (spirals dataset)

We provide:

- **Generate_Spiral_dataset.ipynb** used to generate the spirals dataset.    

- **Spiral_Experiment.ipynb** used to carried out the spirals dataset.

- **data\spirals_datasets** the folder that contains the spirals dataset.

    

### High Dimension

#### Lipschitz Lower Bound

We provide the script **cifar10_lipschitz.py** used to compute $Q(D)$ for Mixup, Local Mixup and Vanilla.

#### CIFAR10 Resnet18

We provide the notebook **cifar.ipynb** used to compute the error rates on Cifar10.

#### Fashion-MNIST DenseNet

We provide the script **fashionmnist.py** used to compute the error rates on Fashion MNIST.

#### SVHN Lenet

We provide the script **svhn.py** used to compute the error rates on MNIST.