Update README.md

README.md

@@ -1,9 +1,27 @@
-# MACE
+<span style="font-size:larger;">MACE</span>
+========
 [![GitHub release](https://img.shields.io/github/release/ACEsuit/mace.svg)](https://GitHub.com/ACEsuit/mace/releases/)
+[![Paper](https://img.shields.io/badge/Paper-NeurIPs2022-blue)](https://openreview.net/forum?id=YPpSngE-ZU)
 [![License](https://img.shields.io/badge/License-MIT%202.0-blue.svg)](https://opensource.org/licenses/mit)
 [![GitHub issues](https://img.shields.io/github/issues/ACEsuit/mace.svg)](https://GitHub.com/ACEsuit/mace/issues/)
-
-
+[![Documentation Status](https://readthedocs.org/projects/mace/badge/)](https://mace-docs.readthedocs.io/en/latest/)
+
+# Table of contents
+- [About MACE](#about-mace)
+- [Documentation](#documentation)
+- [Installation](#installation)
+- [Usage](#usage)
+    - [Training](#training)
+    - [Evaluation](#evaluation)
+- [Tutorial](#tutorial)
+- [Weights and Biases](#weights-and-biases-for-experiment-tracking)
+- [Development](#development)
+- [References](#references)
+- [Contact](#contact)
+- [License](#license)
+
+
+##  About MACE
 MACE provides fast and accurate machine learning interatomic potentials with higher order equivariant message passing.
 
 This repository contains the MACE reference implementation developed by
@@ -13,6 +31,10 @@ Also available:
 * [MACE in JAX](https://github.com/ACEsuit/mace-jax), currently about 2x times faster at evaluation, but training is recommended in Pytorch for optimal performances.
 * [MACE layers](https://github.com/ACEsuit/mace-layer) for constructing higher order equivariant graph neural networks for arbitrary 3D point clouds.
 
+## Documentation
+
+A partial documentation is available at: https://mace-docs.readthedocs.io/en/latest/
+
 ## Installation
 
 Requirements: