Improve formatting of README.md

Author: plainerman

README.md

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-# Doob’s Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
-[![python](https://img.shields.io/badge/language-python%20-%2300599C.svg?style=flat-square)](#)
+<h1 align="center">Doob’s Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling</h1>
+<p align="center">
+<a href="https://github.com/plainerman/variational-doob"><img src="https://img.shields.io/badge/language-python%20-%2300599C.svg?style=flat-square" alt="Built with Python"/></a>
+<a href="https://github.com/jax-ml/jax"><img src="https://img.shields.io/badge/library-JAX-5f0964?style=flat-square" alt="Jax"/></a>
+</p>
+<p align="center">
+A novel variational approach to transition path sampling (TPS) based on the Doob’s h-transform. Our method can be used to sample transition paths between two meta-stable states of molecular systems.
+</p>
 
-In this work, we propose a novel variational approach to transition path sampling (TPS) based on the Doob’s h-transform. Our method can be used to sample transition paths between two meta-stable states of molecular systems.
 
 ![Visualization of alanine dipeptide transitioning between two meta-stable states](visualizations/aldp.gif)