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CORES Annual Symposium 2024

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Symposium 2024: Reproducibility in Machine Learning

May 21, 2024, Stanford University

ChemH-Neuroscience, John A. and Cynthia Fry Gunn Rotunda, E241

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Agenda

12:30pm-1:00pmRegistration and Refreshments 
1:00pm-1:30pm Welcome Address: David Studdert (Vice Provost and Dean of Research) & Russ Poldrack (Albert Ray Lang Professor of Psychology and Director, SDS Center for Open and Reproducible Science) 
1:30pm- 2:30pm Keynote: Improving Reproducibility and Transparency in the Science of AI, Jesse Dodge (Allen Institute for AI) 
2:30pm-3:00pmReproducibility in the Age of Foundation Models, Jessica Forde (PhD Student, Brown University) 
3:00pm-3:30pm Proving Test Set Contamination in Black Box Language Models, Nicole Meister (Stanford University)
3:30pm-3:45pmBreak 
3:45-pm-4:00pmAwards presented by Russell Poldrack 
4:00pm-4:45pm

Panel: Improving the Application of ML/AI in Science 

Moderator: Emma Brunskill, Stanford University

  • Risa Wechsler, Stanford University
  • Matthias Imhe, Stanford University
  • Manisha Desai, Stanford University¬†
4:45pm-5:00pmClosing Remarks 
5:00pm-6:00pmNetworking and Light Refreshments