PriorLabs/tabpfn-extensions
Jan 2025 – Jan 2025
1 Month active
Languages Used
MarkdownPython
Technical Skills
Data ScienceDocumentationInterpretabilityMachine LearningPython
Maximilian
PROFILE
Maximilian
Maximilian Muschalik enhanced the PriorLabs/tabpfn-extensions repository by integrating SHAP-IQ to provide robust Shapley-based interpretability for TabPFN users. He refactored existing Python explainers to support imputation-based explanations and developed an example script demonstrating the computation of Shapley and Shapley interaction values, improving the model explainability workflow. Alongside these data science and machine learning contributions, Maximilian updated the project’s Markdown documentation, clarifying and correcting citations for shapiq and SHAP libraries to ensure accurate user guidance. The work delivered tangible improvements in both interpretability tooling and documentation quality, reflecting a focused and technically sound engineering approach within one month.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
300
Activity Months1
Your Network
17 people
Work History
January 2025
3 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for PriorLabs/tabpfn-extensions. Delivered enhanced interpretability capabilities and documentation improvements that provide tangible business value by enabling robust Shapley-based explanations and clearer guidance for users of the TabPFN extensions.
3 Commits • 2 Features
Jan 1, 2025January 2025 monthly summary for PriorLabs/tabpfn-extensions. Delivered enhanced interpretability capabilities and documentation improvements that provide tangible business value by enabling robust Shapley-based explanations and clearer guidance for users of the TabPFN extensions.
January 2025
Activity
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Quality Metrics
Correctness93.4%
Maintainability93.4%
Architecture93.4%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownPython
Technical Skills
Data ScienceDocumentationInterpretabilityMachine LearningPython
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