Publications

Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

Citation

BibTex format

@article{Cofré:2019:10.3390/e21090884,
author = {Cofré, R and Videla, L and Rosas, F},
doi = {10.3390/e21090884},
journal = {Entropy},
pages = {1--28},
title = {An introduction to the non-equilibrium steady states of maximum entropy spike trains},
url = {http://dx.doi.org/10.3390/e21090884},
volume = {21},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Although most biological processes are characterized by a strong temporal asymmetry, several popular mathematical models neglect this issue. Maximum entropy methods provide a principled way of addressing time irreversibility, which leverages powerful results and ideas from the literature of non-equilibrium statistical mechanics. This tutorial provides a comprehensive overview of these issues, with a focus in the case of spike train statistics. We provide a detailed account of the mathematical foundations and work out examples to illustrate the key concepts and results from non-equilibrium statistical mechanics.
AU  - Cofré,R
AU  - Videla,L
AU  - Rosas,F
DO  - 10.3390/e21090884
EP  - 28
PY  - 2019///
SN  - 1099-4300
SP  - 1
TI  - An introduction to the non-equilibrium steady states of maximum entropy spike trains
T2  - Entropy
UR  - http://dx.doi.org/10.3390/e21090884
UR  - https://www.mdpi.com/1099-4300/21/9/884
UR  - http://hdl.handle.net/10044/1/73582
VL  - 21
ER  -
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