[DOC] adding "how to cite" info

Author: nglm

docs/md/welcome_bottom.md

@@ -9,7 +9,7 @@ If you are having issues, [please let me know](https://www.uib.no/en/persons/Nat
 
 ## How to cite PyCVI
 
-If you are using PyCVI in your work, please cite us using one of the following entries:
+If you are using PyCVI in your work, please cite us by using one of the following entries referring to the JOSS paper *PyCVI: A Python package for internal Cluster Validity Indices, compatible with time-series data* by N. Galmiche:
 
 **BibTeX**:
 

docs/md/welcome_top.md

@@ -1,5 +1,9 @@
 # Welcome to PyCVI's documentation!
 
+[![Python package](https://github.com/nglm/pycvi/actions/workflows/python-package.yml/badge.svg)](https://github.com/nglm/pycvi/actions/workflows/python-package.yml)
+[![Documentation Status](https://readthedocs.org/projects/pycvi/badge/?version=latest)](https://pycvi.readthedocs.io/en/latest/?badge=latest)
+[![status](https://joss.theoj.org/papers/fb63888e0a78da2866b03247ce18909d/status.svg)](https://joss.theoj.org/papers/fb63888e0a78da2866b03247ce18909d)
+
 PyCVI is a Python package specialized in internal Clustering Validity Indices (CVI). Internal CVIs are used to select the best clustering among a set of pre-computed clusterings when no external information is available such as the labels of the datapoints.
 
 Although being fundamental to clustering tasks and being an active research topic, very few internal CVIs are implemented in standard python libraries (only 3 in [scikit-learn](https://scikit-learn.org/stable/index.html), more were available in R but few were maintained and kept in CRAN). This is despite the well-known limitations of all existing CVIs and the need to use the right one(s) according to the specific dataset at hand.