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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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