Merge pull request #50 from TomMago/master

update qmlhep and genie tests

_gsocproposals/2024/proposal_GENIE1.md

@@ -29,8 +29,8 @@ Total project length: 175/350 hours.
   * Trained graph based anomaly detection model
   * Benchmark of on selected datasets
 
-<!-- ## Test 
-Please use [this link](https://docs.google.com/document/d/10C8mNjE-WE6OuESjcnuJ_N430D-Hdtz-4_lLxGMnKbI/edit?usp=sharing) to access the test for this project. -->
+## Test 
+Please use [this link](https://docs.google.com/document/d/142YpKV7fJ49zaBZkSBekbBzw43KD71No2K_Jd-n5Neo/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Skills: Python, PyTorch or TensorFlow and some previous experience in Machine Learning.

_gsocproposals/2024/proposal_GENIE2.md

@@ -29,8 +29,8 @@ Total project length: 175/350 hours.
   * Functional INR model
   * Benchmark results  on selected datasets
 
-<!-- ## Test 
-Please use [this link](https://docs.google.com/document/d/10C8mNjE-WE6OuESjcnuJ_N430D-Hdtz-4_lLxGMnKbI/edit?usp=sharing) to access the test for this project. -->
+## Test 
+Please use [this link](https://docs.google.com/document/d/142YpKV7fJ49zaBZkSBekbBzw43KD71No2K_Jd-n5Neo/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Skills: Python, PyTorch or Keras and some previous experience in Machine Learning. 

_gsocproposals/2024/proposal_GENIE3.md

@@ -28,9 +28,8 @@ Total project length: 175/350 hours.
   * Functional diffusion model
   * Benchmarks on selected datasets
 
-
-<!-- ## Test 
-Please use [this link](https://docs.google.com/document/d/10C8mNjE-WE6OuESjcnuJ_N430D-Hdtz-4_lLxGMnKbI/edit?usp=sharing) to access the test for this project. -->
+## Test 
+Please use [this link](https://docs.google.com/document/d/142YpKV7fJ49zaBZkSBekbBzw43KD71No2K_Jd-n5Neo/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Skills: Python, PyTorch or Keras and some previous experience in Machine Learning. 

_gsocproposals/2024/proposal_GENIE4.md

@@ -29,9 +29,8 @@ Total project length: 175/350 hours.
   * Trained graph-based jet classifier
   * Benchmarks on selected datasets
 
-
-<!-- ## Test 
-Please use [this link](https://docs.google.com/document/d/10C8mNjE-WE6OuESjcnuJ_N430D-Hdtz-4_lLxGMnKbI/edit?usp=sharing) to access the test for this project. -->
+## Test 
+Please use [this link](https://docs.google.com/document/d/142YpKV7fJ49zaBZkSBekbBzw43KD71No2K_Jd-n5Neo/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Skills: Python, PyTorch or Keras and some previous experience in Machine Learning. 

_gsocproposals/2024/proposal_QMLHEP1.md

@@ -29,8 +29,8 @@ Total project length: 175/350 hours.
   * Trained Quantum Generative Adversarial Network method based on e.g. Pennylane framework.
   * Successfully apply the Quantum Machine Learning method to LHC physics analyses and obtain performance benchmarks to compare to classical machine learning methods.
 
-<!-- ## Test
-Please use [this link](https://docs.google.com/document/d/1dqBGbH44Eu3W432oRxpOCfI5Dy2pgh2E21JcHeD0fng/edit?usp=sharing) to access the test for this project. -->
+## Test
+Please use [this link](https://docs.google.com/document/d/1sWHt7miyhFXnFeWmZ_El0P7wiRlggj5WPRktA7dsUh8/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Solid knowledge of machine learning and deep learning

_gsocproposals/2024/proposal_QMLHEP2.md

@@ -28,8 +28,8 @@ Total project length: 175/350 hours.
   * Trained Quantum Graph Neural Network with e.g. Pennylane framework.
   * Apply the Quantum Machine Learning method to LHC physics analysis and compare to classical machine learning methods.
 
-<!-- ## Test
-Please use [this link](https://docs.google.com/document/d/1dqBGbH44Eu3W432oRxpOCfI5Dy2pgh2E21JcHeD0fng/edit?usp=sharing) to access the test for this project. -->
+## Test
+Please use [this link](https://docs.google.com/document/d/1sWHt7miyhFXnFeWmZ_El0P7wiRlggj5WPRktA7dsUh8/edit?usp=sharing) to access the test for this project.
 
 ## Requirements 
   * Solid knowledge of machine learning and deep learning

_gsocproposals/2024/proposal_QMLHEP3.md

@@ -28,9 +28,8 @@ Total project length: 175/350 hours.
   * Trained embedding function for classical data with e.g. Pennylane framework.
   * Benchmark of the performance against a standard encoding
 
-
-<!-- ## Test
-Please use [this link](https://docs.google.com/document/d/1dqBGbH44Eu3W432oRxpOCfI5Dy2pgh2E21JcHeD0fng/edit?usp=sharing) to access the test for this project. -->
+## Test
+Please use [this link](https://docs.google.com/document/d/1sWHt7miyhFXnFeWmZ_El0P7wiRlggj5WPRktA7dsUh8/edit?usp=sharing) to access the test for this project.
 
 ## Requirements
   * Solid knowledge of machine learning and deep learning

_gsocproposals/2024/proposal_QMLHEP4.md

@@ -28,8 +28,8 @@ Total project length: 175/350 hours.
   * Trained equivariant quantum neural networks with e.g. Pennylane framework.
   * Benchmark of the performance against a non-equivariant model
 
-<!-- ## Test
-Please use [this link](https://docs.google.com/document/d/1dqBGbH44Eu3W432oRxpOCfI5Dy2pgh2E21JcHeD0fng/edit?usp=sharing) to access the test for this project. -->
+## Test
+Please use [this link](https://docs.google.com/document/d/1sWHt7miyhFXnFeWmZ_El0P7wiRlggj5WPRktA7dsUh8/edit?usp=sharing) to access the test for this project.
 
 ## Requirements
   * Solid knowledge of machine learning and deep learning

_gsocproposals/2024/proposal_QMLHEP5.md

@@ -28,9 +28,8 @@ Total project length: 175/350 hours.
   * Trained quantum transformer model.
   * Benchmark of the performance on a HEP dataset compared against a classical reference model
 
-
-<!-- ## Test
-Please use [this link](https://docs.google.com/document/d/1dqBGbH44Eu3W432oRxpOCfI5Dy2pgh2E21JcHeD0fng/edit?usp=sharing) to access the test for this project. -->
+## Test
+Please use [this link](https://docs.google.com/document/d/1sWHt7miyhFXnFeWmZ_El0P7wiRlggj5WPRktA7dsUh8/edit?usp=sharing) to access the test for this project.
 
 ## Requirements
   * Solid knowledge of machine learning and deep learning