23 citations · 30 across the 5 of their papers we have counts for
6 papers
Comment on Deterministic Information Bottleneck
Sarah Marzen
We make the case that although Deterministic Information Bottleneck may be a contribution to clustering, it should not be used to aid lossy compression without the addition of bloc…
Complexity-calibrated Benchmarks for Machine Learning Reveal When Next-Generation Reservoir Computer Predictions Succeed and Mislead
Sarah E. Marzen, Paul M. Riechers, James P. Crutchfield
Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form…
Understanding and Designing Complex Systems: Response to "A framework for optimal high-level descriptions in science and engineering---preliminary report"
James P. Crutchfield, Ryan G. James, Sarah Marzen +1
We recount recent history behind building compact models of nonlinear, complex processes and identifying their relevant macroscopic patterns or "macrostates". We give a synopsis of…
Circumventing the Curse of Dimensionality in Prediction: Causal Rate-Distortion for Infinite-Order Markov Processes
Sarah Marzen, James P. Crutchfield
Predictive rate-distortion analysis suffers from the curse of dimensionality: clustering arbitrarily long pasts to retain information about arbitrarily long futures requires resour…
Information Anatomy of Stochastic Equilibria
Sarah Marzen, James P. Crutchfield
A stochastic nonlinear dynamical system generates information, as measured by its entropy rate. Some---the ephemeral information---is dissipated and some---the bound information---…
An equivalence between a Maximum Caliber analysis of two-state kinetics and the Ising model
Sarah Marzen, Dave Wu, Mandar Inamdar +1
Application of the information-theoretic Maximum Caliber principle to the microtrajectories of a two-state system shows that the determination of key dynamical quantities can be ma…