From d010a688730917ef529a6684018271119cf770a8 Mon Sep 17 00:00:00 2001
From: karine <76127656+karineML@users.noreply.github.com>
Date: Wed, 5 Apr 2023 12:22:34 -0400
Subject: [PATCH] update examples

update examples
---
 Examples/README.md | 27 ++++++++++++++++++++++++++-
 1 file changed, 26 insertions(+), 1 deletion(-)

diff --git a/Examples/README.md b/Examples/README.md
index 0f7b1fb..2aab323 100644
--- a/Examples/README.md
+++ b/Examples/README.md
@@ -1,6 +1,31 @@
-# BayesLDM Examples
+# BayesLDM
+
+This repository contains the official implementation for the BayesLDM paper. 
+This work is supported by National Institutes of Health through grants U01CA229445 and 1P41EB028242.
+The paper was accepted at IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2022. 
+
+## Examples
+
+See the [Examples](https://github.com/reml-lab/BayesLDM/tree/main/Examples) directory for a list of BayesLDM examples that can be run locally or launched in Google Colab.
+
+For example:
 
 + [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/reml-lab/BayesLDM/blob/main/Examples/BayesLDM_quickstart.ipynb)  BayesLDM Quickstart
 
 + [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/reml-lab/BayesLDM/blob/main/Examples/BayesLDM_userguide.ipynb)  BayesLDM User Guide
 
+## Citing BayesLDM
+
+If you use BayesLDM, please cite our paper. 
+
+This paper was accepted at IEEE/ACM international conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE) 2022. 
++ The link for the published paper is: [paper link](https://ieeexplore.ieee.org/document/9983643)
++ The link for the arXiv paper is: [arXiv link](https://arxiv.org/abs/2209.05581)
+
+@inproceedings{BayesLDM2022,
+  author={Tung, Karine and De La Torre, Steven and El Mistiri, Mohamed and De Braganca, Rebecca Braga and Hekler, Eric and Pavel, Misha and Rivera, Daniel and Klasnja, Pedja and Spruijt-Metz, Donna and Marlin, Benjamin M.},
+  booktitle={2022 IEEE/ACM Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE)}, 
+  title={BayesLDM: A Domain-specific Modeling Language for Probabilistic Modeling of Longitudinal Data}, 
+  year={2022},
+  pages={78-90}}
+