🐻 My name is Marcel Robeer, and I am currently pursuing a PhD in Explainable Artificial Intelligence (XAI) at Utrecht University!
🤖 My thesis projects and scientific research projects have resulted in several open-source Python packages:
- Explabox: {
Explore|Examine|Explain|Expose} your AI model with the explabox! JOSS Paper.
- GlobalCausalAnalysis: Explaining Model Behavior with Global Causal Analysis (give a causal overview of how aspects such as task-related features, fairness and robustness relate to black-box model behavior). xAI 2023 Paper
.
- text_explainability: A generic explainability architecture for explaining text machine learning models.
- text_sensitivity: Extension of text_explainability for sensitivity testing (robustness & fairness).
- CounterfactualGAN: Generating realistic natural language counterfactuals for classifiers and regressors, without requiring explainee intervention. EMNLP 2021 Paper.
- ContrastiveExplanation: Contrastive and counterfactual explanations for machine learning with Foil Trees. WHI 2018 Paper.
- VisualNarrator: Turns user stories into a conceptual model containing entities and relationships. RE 2016 Paper.
💻 Check out marcelrobeer.github.io for a full overview. See you there!