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World of Software > Computing > Reconstruction Evaluations Across Varying Amounts of Training Data: Mindeye2 | HackerNoon
Computing

Reconstruction Evaluations Across Varying Amounts of Training Data: Mindeye2 | HackerNoon

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Last updated: 2025/04/15 at 12:18 PM
News Room Published 15 April 2025
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Here, we present a further analysis of how model performance scales with training data. All of the results presented in Figures 6, 7, and 8 are calculated on only subject 1.

Authors:

(1) Paul S. Scotti, Stability AI and Medical AI Research Center (MedARC);

(2) Mihir Tripathy, Medical AI Research Center (MedARC) and a Core contribution;

(3) Cesar Kadir Torrico Villanueva, Medical AI Research Center (MedARC) and a Core contribution;

(4) Reese Kneeland, University of Minnesota and a Core contribution;

(5) Tong Chen, The University of Sydney and Medical AI Research Center (MedARC);

(6) Ashutosh Narang, Medical AI Research Center (MedARC);

(7) Charan Santhirasegaran, Medical AI Research Center (MedARC);

(8) Jonathan Xu, University of Waterloo and Medical AI Research Center (MedARC);

(9) Thomas Naselaris, University of Minnesota;

(10) Kenneth A. Norman, Princeton Neuroscience Institute;

(11) Tanishq Mathew Abraham, Stability AI and Medical AI Research Center (MedARC).

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