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Sarah Marzen – Physics

Professor Marzen published the following articles:

·      “Prediction and Dissipation in Nonequilibrium Molecular Sensors: Conditionally Markovian Channels Driven by Memoryful Environments,” Bulletin of Mathematical Biology, Volume 82, Article number: 25 (2020);

·      Uppal, V. Ferdinand, and S. Marzen. “Inferring an observer’s strategy in sequence learning experiments”, Entropy 22(8), 896 (2020).  Chosen as a Featured Article for a Special Issue on Social Processes;

·      M. Razo-Mejia, S. Marzen, G. Chure, R. Taubman, M. Morrison, and R. Phillips. “First-principles prediction of the information processing capacity of a simple genetic circuit”, Physical Review E 102, 022404 (2020).  Chosen as an Editor’s Suggestion.

 

 

She presented the following talks:

·      “New Methods for Continuous-time, Discrete-event Prediction” at Singapore’s Nanyang Technological University, Workshop on Agency;

·      “How Can We Predict Efficiently?” at an Okinawa Institute of Technology Seminar;

·      “Using Lossy Representations to Understand the Neural Code” at the Organization for Computational Neuroscience’s Information Theory Workshop;

·      “How Can We Predict Efficiently?” at a University of California San Diego seminar.

 

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