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-[Interpretable machine learning for precision cognitive aging](https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2025.1560064/full)
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-[LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs](https://arxiv.org/pdf/2308.01157.pdf)
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-[Model Interpretability in Credit Insurance](http://hdl.handle.net/10400.5/27507)
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-[Enhancing ML Interpretability for Credit Scoring](https://arxiv.org/html/2509.11389v1)
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-[Transparent and Fair Profiling in Employment Services: Evidence from Switzerland](https://www.arxiv.org/pdf/2509.11847)
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-[Federated Boosted Decision Trees with Differential Privacy](https://arxiv.org/pdf/2210.02910.pdf)
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-[Differentially private and explainable boosting machine with enhanced utility](https://www.sciencedirect.com/science/article/abs/pii/S0925231224011950?via%3Dihub#preview-section-abstract)
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-[Balancing Explainability and Privacy in Bank Failure Prediction: A Differentially Private Glass-Box Approach](https://ieeexplore.ieee.org/abstract/document/10818483)
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