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structured data that prevails in governments, humanitarian organizations, enterprises, and healthcare. The anticipated research will focus on developing mechanisms for reliable and responsible AI-powered data
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inductive biases, we aim to identify key mechanisms that drive rapid learning in the visual system. The goal is to create a robust mechanistic neural network model of the visual system that not only mimics
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the Table Representation Learning Lab and is member of the Database Architectures group. Prior to joining CWI, she was a postdoctoral fellow at UC Berkeley after obtaining her PhD from the University
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the developmental stages of human infants. By comprehensively measuring and documenting these developmental stages and the associated inductive biases, we aim to identify key mechanisms that drive rapid learning in