====== Programming Assignment I======
Select one of the assignments below.
Assignments marked with {{:courses:xai:winner.png?25|}} can be extended as a continution in Programming Assgnment II.
Projects marked with {{:courses:xai:contract.png?25|}} can be (with some additional work and depending on the results) published as scientific papers.
===== SHAP for time series  =====
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Main goal of the project is to take the code: https://github.com/sbobek/WindowSHAP/tree/main
And add possibility of adding dynamic windows using ruptures point-detection algorithm.
===== Actionable SHAP =====
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The goal of this project is to use shapley values to find counterfactual explanations.
===== Self-explainable Neural Networks =====
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The goal of this project is to reproduce results from {{ :courses:xai:ximl2023_exploring_multi_task_learning_for_explainability_aueb.pdf |Exploring Multi-Task Learning for Explainability}}


===== Lux on Mushrooms datset =====
The goal of this work is to test how LUX works on the Mushroom daatset.
  * Dataset: [[https://archive.ics.uci.edu/dataset/848/secondary+mushroom+dataset|Download]]
  * Example preprocessing: [[https://colab.research.google.com/drive/1o7svANZLp5AGH0mvN906OG4QGCyi26I5|Colab Notebook]]
===== XAI for affective computing =====

The goal of this project is to calculate various XAI models for affective prediciton models
  * Start with the model: [[https://colab.research.google.com/drive/19xlYqtoGz80M6fHmOQsE7TAFf2xyPt9b?usp=sharing|Colab model for LSTMConv1 models]]


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