1 citations · 2 across the 9 of their papers we have counts for
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Reconstructing Training Data From Real World Models Trained with Transfer Learning
Yakir Oz, Gilad Yehudai, Gal Vardi +3
Current methods for reconstructing training data from trained classifiers are restricted to very small models, limited training set sizes, and low-resolution images. Such restricti…
The Wisdom of a Crowd of Brains: A Universal Brain Encoder
Roman Beliy, Navve Wasserman, Amit Zalcher +1
Image-to-fMRI encoding is important for both neuroscience research and practical applications. However, such "Brain-Encoders" have been typically trained per-subject and per fMRI-d…
Functional Brain-to-Brain Transformation with No Shared Data
Navve Wasserman, Roman Beliy, Roy Urbach +1
Combining Functional MRI (fMRI) data across different subjects and datasets is crucial for many neuroscience tasks. Relying solely on shared anatomy for brain-to-brain mapping is i…