CORES Annual Symposium 2024: Reproducibility in Machine Learning

CORES Annual Symposium 2024: Reproducibility in Machine Learning

A half-day symposium on reproducibility in machine learning, hosted by the Stanford Center for Open and REproducible Science (CORES).

By Stanford Data Science

Date and time

Tuesday, May 21 · 1 - 5pm PDT

Location

John A. and Cynthia Fry Gunn Rotunda, E241 at the ChEM-H / Neuro research complex

290 Jane Stanford Way Neuroscience Building (East Wing), 2nd floor Stanford, CA 94305

About this event

  • 4 hours

Machine learning and AI methods are increasingly being used in scientific contexts. While these techniques can often enable novel discoveries in powerful ways, they also have the potential to result in conclusions that are not reproducible or generalizable. This symposium will bring together several speakers from diverse perspectives to discuss how machine learning and AI can endanger reproducibility and reduce bias, and how they can be used more effectively to power discoveries that will stand the test of time.

View the Agenda here (subject to change)

Tickets

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Organized by

Stanford Data Science