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Pascal Sturmfels

PhD Student in Machine Learning

University of Washington

Biography

I am currently a PhD student at the University of Washington, advised by Su In Lee. I am interested in developing methods to make machine learning models more interpretable, and applying such methods to understand biological and health data.

Outside of work I spend time playing piano, and occasionally attending my father’s talks.

Interests

  • Machine Learning
  • Explainable AI

Education

  • PhD in Artificial Intelligence, Current

    Stanford University

  • B.E. in Computer Science, 2017

    University of Michigan

Recent Publications

Explaining Explanations: Axiomatic Feature Interactions for Deep Networks

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Visualizing the Impact of Feature Attribution Baselines

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Automated brain masking of fetal functional MRI

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Learning explainable models using attribution priors

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See all publications

Projects

Path Explanations

A GitHub package to explain not only which features are most important to a neural network prediction, but also how those features interact with each other.

Attribution Priors

A GitHub package to regularize a neural network’s feature attributions during training in order to encode human-level prior knowledge into the training process.