39 citations · 46 across the 10 of their papers we have counts for
4 papers · 2 filters
Prediction and Power in Molecular Sensors: Uncertainty and Dissipation When Conditionally Markovian Channels Are Driven by Semi-Markov Environments
Sarah E. Marzen, James P. Crutchfield
Sensors often serve at least two purposes: predicting their input and minimizing dissipated heat. However, determining whether or not a particular sensor is evolved or designed to…
Intrinsic computation of a Monod-Wyman-Changeux molecule
Sarah Marzen
Causal states are minimal sufficient statistics of prediction of a stochastic process, their coding cost is called statistical complexity, and the implied causal structure yields a…
Structure and Randomness of Continuous-Time Discrete-Event Processes
S. E. Marzen, J. P. Crutchfield
Loosely speaking, the Shannon entropy rate is used to gauge a stochastic process' intrinsic randomness; the statistical complexity gives the cost of predicting the process. We calc…
Nearly Maximally Predictive Features and Their Dimensions
Sarah E. Marzen, James P. Crutchfield
Scientific explanation often requires inferring maximally predictive features from a given data set. Unfortunately, the collection of minimal maximally predictive features for most…