Vig GNN content is updated with video and PDF

README.md

@@ -25,6 +25,7 @@ Join my YouTube Channel for <a href="https://www.youtube.com/channel/UClLqLPWRst
 <hr>
 
 ## ##
+- [PyTorch Tutorials](https://github.com/prodramp/DeepWorks/tree/main/PyTorchTutorials)
 - [GraphViz](https://github.com/prodramp/DeepWorks/tree/main/DeepViz)
 - [Graph Neural Networks](https://github.com/prodramp/DeepWorks/tree/main/GraphNeuralNetworks)
 - [Topic Modeling](https://github.com/prodramp/DeepWorks/tree/main/TopicModelling)
@@ -33,4 +34,5 @@ Join my YouTube Channel for <a href="https://www.youtube.com/channel/UClLqLPWRst
 - [Number Series and Prediction with ML](https://github.com/prodramp/DeepWorks/tree/main/PredictNumberSeries)
 - [GPT Models (OpenAI and OpenSource)](https://github.com/prodramp/DeepWorks/tree/main/GPT-Models)
 - [No More Blackbox Models: MLI or XAI](https://github.com/prodramp/DeepWorks/tree/main/MLI-XAI)
+- [Vision GNN: An Image is Worth Graph of Nodes](https://github.com/prodramp/DeepWorks/tree/main/ViG(VisionGNN))
 

ViG(VisionGNN)/README.md

@@ -1,6 +1,21 @@
 # Vision GNN: An Image is Worth Graph of Nodes # 
 A novel way to represent image patches as Graph to perform image recognition and object detection tasks
 
+The PDF document related to the following video is attached [here](https://github.com/prodramp/DeepWorks/tree/main/ViG(VisionGNN)/ViG-GNN.pdf). 
+<table class="table table-striped table-bordered table-vcenter">
+    <tr>
+        <td align="center"><b>🔥&nbsp;YouTube Video:&nbsp; Research Paper Deep Dive - Vision GNN: An Image is Worth Graph of Nodes</b></td>
+    </tr>
+    <tr>
+        <td>
+            <div>
+                
+[![Research Paper Deep Dive - Vision GNN: An Image is Worth Graph of Nodes](https://img.youtube.com/vi/EzRFPv2JFUM/0.jpg)](https://www.youtube.com/watch?v=EzRFPv2JFUM)
+
+  </tr>
+</table>
+
+
 <div align="center">
   <img src="https://github.com/prodramp/DeepWorks/blob/main/ViG(VisionGNN)/images/vig-gnn.png?raw=true" width="1000" />
 </div>