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Gabriel Stechschulte
Software engineer working on probabilistic programming, Bayesian methods, and optimization; re-implemented BART in Rust to improve performance and scalability for real-world applications.
Best podcasts with Gabriel Stechschulte
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Oct 2, 2025
• 1h 10min
#142 Bayesian Trees & Deep Learning for Optimization & Big Data, with Gabriel Stechschulte
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Gabriel Stechschulte is a software engineer specializing in Bayesian methods and optimization. He discusses the power of Bayesian Additive Regression Trees (BART) for uncertainty quantification and its re-implementation in Rust, enhancing performance for big data. Gabriel explores how BART contrasts with other models, its strengths in avoiding overfitting, and its integration into optimization frameworks for decision-making. He also emphasizes the importance of open-source communities, encouraging newcomers to contribute actively.
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