This paper fuses ideas from both information theory and game theory to study repeated games with incomplete information in a “high-probability framework.”
This paper introduces an information-based model of signal detection motivated by the question of racial discrimination in decision-making scenarios such as police arrests.
By J. Tantiongloc, D. A. Mesa, R. Ma, S. Kim, C. H. Alzate, J. J. Camacho, V. Manian, and T. P. Coleman
This paper presents a framework for a human–computer interface, which provides a simplified method based on optimal transport theory to generate optimal feedback signals between the computer and human in high dimension.
This paper develops the argument that information-theoretic model selection metrics should be extended to nonnested model comparison applications in systems biology.
By S. Mohammadi, N. Zuckerman, A. Goldsmith, and A. Grama
This paper focuses on in silico deconvolution of signals associated with complex tissues into their constitutive cell-type components and surveys a variety of models, methods, and assumptions underlying deconvolution techniques.
This paper explores potential advantages of high-density EEG systems for high- resolution imaging of the brain and proposes a hierarchical sensing technique.