Jordan W. Suchow
University of California, Berkeley
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Publication
Featured researches published by Jordan W. Suchow.
Trends in Cognitive Sciences | 2017
Jordan W. Suchow; David Bourgin; Thomas L. Griffiths
Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity.
Cognitive Science | 2016
Jordan W. Suchow; Thomas L. Griffiths
international conference on learning representations | 2018
Joshua Peterson; Krishan Aghi; Jordan W. Suchow; Alexander Ku; Thomas L. Griffiths
arXiv: Learning | 2018
Max Simchowitz; Kevin G. Jamieson; Jordan W. Suchow; Thomas L. Griffiths
arXiv: Computer Vision and Pattern Recognition | 2018
Joshua Peterson; Jordan W. Suchow; Thomas L. Griffiths
Archive | 2018
Alex Paxton; Jordan W. Suchow; Thomas J. H. Morgan; Thomas L. Griffiths
Journal of Vision | 2018
Joshua Peterson; Krishan Aghi; Jordan W. Suchow; Alexander Ku; Thomas L. Griffiths
Journal of Vision | 2018
Jordan W. Suchow; Joshua Peterson; Thomas L. Griffiths
Journal of Vision | 2017
Malerie McDowell; Jordan W. Suchow; Jason Haberman
Cognitive Science | 2017
Monica A. Gates; Jordan W. Suchow; Thomas L. Griffiths