Predict Man of the Match using various machine learning techniques and explain misclassifications
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Updated
Jun 3, 2019 - Jupyter Notebook
Predict Man of the Match using various machine learning techniques and explain misclassifications
Visualization techniques overview for CNNs - computer vision models, RNNs - natural language processing models, and generic explainability methods.
Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "Explainability Techniques for Graph Convolutional Networks" (ICML19)
Interpretations on the HPA dataset.
A curated list of awesome contrastive explanation in ML resources
Contextual Explanation Networks (CEN).
General-purpose library for extracting interpretable models from Multi-Agent Reinforcement Learning systems
BKT Explainable Game Made in Unity
Code for the experiment proposed in Section 4.2 of the paper "The Bouncer Problem: Challenges to Remote Explainability".
Analysis and investigating the confounding effect of accents in end-to-end Automatic Speech Recognition models.
Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
Master's thesis in Human explainability through an auxiliary Neural Network
Master Thesis project of the Masters in Data Science of the University of Barcelona
Data generator for Arena - interactive XAI dashboard
Visual Exploration of Representations Learned by Convolutional Neural Networks
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