diff --git a/README.md b/README.md index 69258ef..3907c12 100644 --- a/README.md +++ b/README.md @@ -1,22 +1,24 @@
-# jax-influence +## JAX-Influence [![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE.txt)
-jax-influence is a Jax implementation of influence functions, a classical -technique from robust statistics that estimates the effect of removing a single training data point on a model’s -learned parameters. The code is supplement to the paper [If Influence Functions are the Answer, Then What is the Question?](https://arxiv.org/abs/2209.05364). +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?"](https://arxiv.org/abs/2209.05364). -This library aims to be simple and minimal. Furthermore, the PyTorch implementation can be found at [here](https://github.com/alstonlo/torch-influence). +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](https://github.com/alstonlo/torch-influence), and +a PyTorch EK-FAC implementation can be found [here](https://github.com/pomonam/kronfluence). ______________________________________________________________________ ## Installation -Pip from source: +To install JAX-Influence, you can use pip to install from the source: ```bash git clone https://github.com/pomonam/jax-influence @@ -28,16 +30,8 @@ pip install -e '.[jax_gpu]' -f 'https://storage.googleapis.com/jax-releases/jax_ ______________________________________________________________________ -## Quickstart - -### Overview - -An end-to-end example can be found in `tests`. We will add more examples in the future, including PBRF computation. - -______________________________________________________________________ - ## Contributors - [Juhan Bae](https://www.juhanbae.com/) -- [Nathan Ng](https://scholar.google.com/citations?user=psuwztYAAAAJ&hl=en) -- [Alston Lo](https://github.com/alstonlo) +- [Nathan Ng](https://nng555.github.io/) +- [Alston Lo](https://alstonlo.github.io/)