Dylan M Paiton, PhD

Affiliations:	2007-2011	Electrical Engineering	New Mexico Institute of Mining and Technology
	2011-2013		Los Alamos National Laboratory, Los Alamos, NM, United States
	2013-2019	Vision Science	University of California, Berkeley, Berkeley, CA, United States
	2019-2021	Theoretical Physics	Eberhard Karls Universität Tübingen, Tübingen, Baden-Württemberg, Germany

Area:

vision science, artificial intelligence, machine learning, visual neuroscience

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"Dylan Paiton"

Bio:

How does our visual system convert noisy signals into what we perceive? How does the brain represent the world in a way that is both efficient and useful? These questions are what motivate my research. I analyze model neural networks to develop hypotheses for the functional roles of feedback and lateral connectivity in cortex. I study how the class of nonlinearities used for artificial neurons shape their response properties and expressive power. I also develop probabilistic hierarchical models of natural images to advance theoretical frameworks for how we see.

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