updated the image references in README to reference the ones on github (

#48)

* updated the image references in README to reference the ones on github
* updated pyproject.toml to include additional authors

README.md

@@ -25,7 +25,7 @@ days and 365 days, ATTs are in the form of **$M_n$** where n represents the mont
    concepts
    associated with the visit are subsumed by **VS** and **VE**.
 
-!["patient_representation"](images/tokenization_att_generation.png)
+!["patient_representation"](https://raw.githubusercontent.com/cumc-dbmi/cehr-bert/main/images/tokenization_att_generation.png)
 
 ## Model Architecture
 
@@ -36,7 +36,7 @@ connected layer. This temporal concept embedding becomes the input to BERT. We u
 Language Model as the primary learning objective and introduced an EHR specific secondary learning objective visit type
 prediction.
 
-!["cehr-bert architecture diagram"](images/cehr_bert_architecture.png)
+!["cehr-bert architecture diagram"](https://raw.githubusercontent.com/cumc-dbmi/cehr-bert/main/images/cehr_bert_architecture.png)
 
 ## Pre-requisite
 

pyproject.toml

@@ -8,7 +8,9 @@ dynamic = ["version"]
 authors = [
     { name = "Chao Pang", email = "[email protected]" },
     { name = "Xinzhuo Jiang", email = "[email protected]" },
-    { name = "Krishna Kalluri", email = "[email protected]" }
+    { name = "Krishna Kalluri", email = "[email protected]" },
+    { name = "Nishanth Parameshwar Pavinkurve", email = "[email protected]" },
+    { name = "Karthik Natarajan", email = "[email protected]" }
 ]
 description = "CEHR-BERT: Incorporating temporal information from structured EHR data to improve prediction tasks"
 readme = "README.md"