Update README.md

Quantum Vision/README.md

@@ -1,26 +1,21 @@
-Fill in this README.md. Example Structure:
-
 ## Project Description 
-(3-4 lines about what it is and how you did it)
-
-## Setup
-Example:
-1. Make sure you have X installed and configured.
+The inference method based on the maximum entropy principle (MaxEnt principle) asserts that the most suitable probability distribution compatible with a given set of constraints is the one with the largest entropy. This method is considered as a powerful estimation technique in a wide range of probabilistic models since it brings a solution to the universal problem of trying to stract information from partial or incomplete data.
 
-2. Set up your preferred virtual environment.
+Finding the MaxEnt probability distribution is considered a hard task due to the nonlinearities in the reconstruction algorithm. We have redefined the MaxEnt problem as a QUBO problem using a linearized entropy. As a proof of concept, we present a code that finds the MaxEnt probability distribution given the appearance frequencies of the faces of a dice as constraints. 
 
-3. pip install -r requirements.txt
+## Setup
+- Make sure you have Ocean installed and configured. Follow the [instructions](https://docs.ocean.dwavesys.com/en/latest/overview/install.html).
+- You need to have Jupyter Notebook installed. If you do not have it installed, follow this [instructions](https://jupyter.org/install).
 
 ## How to Use
-Example:
-From command line: Use python solvers/script.py -h
+To see the example showed in the code, all you need to do is run the cells pressing Shift+Enter.
 
 ## Challenge(s) You Solved
+We proposed a solution for the DWave challenge.
 
-## Project Details: 
-  - Further walkthrough of what you did 
-  - Links to any Jupyter notebooks/scripts
-  - Business applications
-  - Link to Presentation
+## Project Details:  
+  - [Link to Jupyter notebooks](./QuantumVision.ipynb)
+  - [Link to Presentation](./2021-CDL_MaxEnt_V2.pdf)
 
 ## Contributors 
+Inés Corte, Federico Holik, Marcelo Losada, Lorena Rebón, Diego Tielas