Codebase for Inducing Causal Structure for Interpretable Neural Networks

Last update: Oct 10, 2022

Overview

Interchange Intervention Training (IIT)

Codebase for Inducing Causal Structure for Interpretable Neural Networks

Release Notes

12/01/2021: Code and Paper are initially released. Stay tuned for complete implementation for all case studies.

Installation

First clone the directory. Then run the following command to initialize the submodules:

git submodule init; git submodule update

Each time pulling from the repository, should do it for both the main repository and the submodules. You can also do it via our script:

bash pull.sh

Usage

You will find examples where we implement interchange intervention training (IIT) under ./examples folder.

Owner

Zen

GitHub Repository

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Codebase for Inducing Causal Structure for Interpretable Neural Networks

Related tags

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Interchange Intervention Training (IIT)

Release Notes

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Usage

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Zen

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Codebase for Inducing Causal Structure for Interpretable Neural Networks

Related tags

Overview

Interchange Intervention Training (IIT)

Release Notes

Installation

Usage

Owner

Zen

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Some methods for comparing network representations in deep learning and neuroscience.

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StarGAN2 for practice

Code of 3D Shape Variational Autoencoder Latent Disentanglement via Mini-Batch Feature Swapping for Bodies and Faces

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