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Sarah Marzen- Physics

Professor Sarah Marzen has contributed the following:

Guest Editor for Computational Brain and Behavior Special Issue on “Sensory Prediction: Engineered and Evolved”

Guest Editor for Open Mind Special Issue on “Information-Theoretic Principles in Cognitive Systems”

Co-organized SFI/NSF/Keck Workshop on Sensory Prediction: Engineered and Evolved that was featured in SFI Parallax

Papers:

  1. Sawaya∗, G. Issa∗, and S. Marzen. “A framework for solving time-delayed Markov Decision Processes”, Physical Review Research 5 (2023)
  2. Lamberti∗, S. Tripathi∗, M. van Putten, S. Marzen, and J. le Feber. “Prediction in cultured cortical neural networks”, PNAS Nexus 2(6) (2023)

Invited Talks:

  1. Marzen. “How well do neurons, humans, and artificial neural networks predict?” Organization of Computational Neuroscience Workshop on Information Theory (2023)
  2. Marzen. “How well do neurons, humans, and artificial neural networks predict?” Santa Fe Institute Workshop on Sensory Prediction, Engineered and Evolved (2023)
  3. Marzen. “How well do neurons, humans, and artificial neural networks predict?” American Mathematical Society, Sectional Meeting (2023)

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