pomonam / jax-influence Goto Github PK

JAX-Influence is a JAX implementation of influence functions, a classical technique from robust statistics that estimates the impact of removing a single training data point on a model's learned parameters. This repository complements the paper "If Influence Functions are the Answer, Then What is the Question?".

The repository aims to provide a simple and minimal implementation of influence functions in JAX. For those interested in implementations in other frameworks, a PyTorch version is available here, and a PyTorch EK-FAC implementation can be found here.

To install JAX-Influence, you can use pip to install from the source:

git clone https://github.com/pomonam/jax-influence
 
cd jax-influence
pip install -e .   
pip install -e '.[jax_gpu]' -f 'https://storage.googleapis.com/jax-releases/jax_cuda_releases.html' # Replace `jax_gpu` with `jax_cpu` if you wish to install the CPU version.

• Juhan Bae
• Nathan Ng
• Alston Lo