Editing a classifier by rewriting its prediction rules

Last update: Dec 27, 2022

Related tags

Overview

This repository contains the code and data for our paper:

Editing a classifier by rewriting its prediction rules
Shibani Santurkar*, Dimitris Tsipras*, Mahi Elango, David Bau, Antonio Torralba, Aleksander Madry
Paper: https://arxiv.org/abs/2112.01008

    @InProceedings{santurkar2021editing,
        title={Editing a classifier by rewriting its prediction rules},
        author={Shibani Santurkar and Dimitris Tsipras and Mahalaxmi Elango and David Bau and Antonio Torralba and Aleksander Madry},
        year={2021},
        booktitle={Neural Information Processing Systems (NeurIPS)}
    }

Getting started

You can start by cloning our repository and following the steps below. Parts of this codebase have been derived from the GAN rewriting repository of Bau et al.

Install the dependencies for our code using Conda. You may need to adjust the environment YAML file depending on your setup.
```
conda env create -f environment.yaml
```
Download model checkpoints and extract them in the current directory.

To instantiate CLIP

git submodule init
git submodule update

Replace IMAGENET_PATH in helpers/classifier_helpers.py with the path to the ImageNet dataset.
(If using synthetic examples) Download files segmentations.tar.gz and styles.tar.gz and extract them under ./data/synthetic.
(If using synthetic examples) Run

     python stylize.py --style_name [STYLE_FILE_NAME]

with the desired style file from ./data/synthetic/styles. You could also use a custom style file if desired.

That's it! Now you can explore our editing methodology in various settings: vehicles-on-snow, typographic attacks and synthetic test cases.

Maintainers

Simple embedding based text classifier inspired by fastText, implemented in tensorflow

FastText in Tensorflow This project is based on the ideas in Facebook's FastText but implemented in Tensorflow. However, it is not an exact replica of

306 Dec 2, 2022

CondNet: Conditional Classifier for Scene Segmentation

CondNet: Conditional Classifier for Scene Segmentation Introduction The fully convolutional network (FCN) has achieved tremendous success in dense vis

31 Jul 22, 2022

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples This project is for the paper "Training Confidence-Calibrated Clas

168 Nov 29, 2022

Open-Set Recognition: A Good Closed-Set Classifier is All You Need

Open-Set Recognition: A Good Closed-Set Classifier is All You Need Code for our paper: "Open-Set Recognition: A Good Closed-Set Classifier is All You

194 Jan 3, 2023

The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

Published by SpaceML • About SpaceML • Quick Colab Example Self-Supervised Learner The Self-Supervised Learner can be used to train a classifier with

92 Nov 30, 2022

This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization This codebase is the official implementation of Test-Time Classifier A

47 Dec 28, 2022

A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.

3 Dec 29, 2022

Training Cifar-10 Classifier Using VGG16

opevcvdl-hw3 This project uses pytorch and Qt to achieve the requirements. Version Python 3.6 opencv-contrib-python 3.4.2.17 Matplotlib 3.1.1 pyqt5 5.

3 Aug 17, 2022

Yoga - Yoga asana classifier for python

Yoga Asana Classifier Description Hi welcome to my new deep learning project "Yo

35 Dec 12, 2022

Editing a classifier by rewriting its prediction rules

Related tags

Overview

Getting started

Maintainers

You might also like...

Simple embedding based text classifier inspired by fastText, implemented in tensorflow

CondNet: Conditional Classifier for Scene Segmentation

Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018

Open-Set Recognition: A Good Closed-Set Classifier is All You Need

The Self-Supervised Learner can be used to train a classifier with fewer labeled examples needed using self-supervised learning.

This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.

Training Cifar-10 Classifier Using VGG16

Yoga - Yoga asana classifier for python

Releases(v1)

v1(Dec 2, 2021)

Owner

Madry Lab

The (Official) PyTorch Implementation of the paper "Deep Extraction of Manga Structural Lines"

Code for "On Memorization in Probabilistic Deep Generative Models"

Artificial Neural network regression model to predict the energy output in a combined cycle power plant.

Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domains.

3D Generative Adversarial Network

[NeurIPS 2020] Official Implementation: "SMYRF: Efficient Attention using Asymmetric Clustering".

Bidimensional Leaderboards: Generate and Evaluate Language Hand in Hand

Measuring and Improving Consistency in Pretrained Language Models

FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection

Code repo for "FASA: Feature Augmentation and Sampling Adaptation for Long-Tailed Instance Segmentation" (ICCV 2021)

PyTorch implementation of a Real-ESRGAN model trained on custom dataset

Json2Xml tool will help you convert from json COCO format to VOC xml format in Object Detection Problem.

Simple transformer model for CIFAR10

AbelNN: Deep Learning Python module from scratch

Code for "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clouds", CVPR 2021

MOpt-AFL provided by the paper "MOPT: Optimized Mutation Scheduling for Fuzzers"

Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentation, CVPR 2018

DexterRedTool - Dexter's Red Team Tool that creates cronjob/task scheduler to consistently creates users

Detect roadway lanes using Python OpenCV for project during the 5th semester at DHBW Stuttgart for lecture in digital image processing.

Unofficial PyTorch Implementation of "Augmenting Convolutional networks with attention-based aggregation"