Christopher John Quinn
Title
Cited by
Cited by
Year
Estimating the directed information to infer causal relationships in ensemble neural spike train recordings
CJ Quinn, TP Coleman, N Kiyavash, NG Hatsopoulos
Journal of computational neuroscience 30 (1), 17-44, 2011
2302011
Directed information graphs
CJ Quinn, N Kiyavash, TP Coleman
IEEE Transactions on information theory 61 (12), 6887-6909, 2015
1182015
Design, fabrication and analysis of a body-caudal fin propulsion system for a microrobotic fish
KJ Cho, E Hawkes, C Quinn, RJ Wood
2008 IEEE international Conference on Robotics and Automation, 706-711, 2008
752008
Crowdsourcing high quality labels with a tight budget
Q Li, F Ma, J Gao, L Su, CJ Quinn
Proceedings of the ninth acm international conference on web search and data …, 2016
462016
Efficient methods to compute optimal tree approximations of directed information graphs
CJ Quinn, N Kiyavash, TP Coleman
IEEE Transactions on Signal Processing 61 (12), 3173-3182, 2013
312013
Dynamic and succinct statistical analysis of neuroscience data
S Kim, CJ Quinn, N Kiyavash, TP Coleman
Proceedings of the IEEE 102 (5), 683-698, 2014
292014
Fingerprinting with equiangular tight frames
DG Mixon, CJ Quinn, N Kiyavash, M Fickus
IEEE Transactions on Information Theory 59 (3), 1855-1865, 2013
272013
Equivalence between minimal generative model graphs and directed information graphs
CJ Quinn, N Kiyavash, TP Coleman
2011 IEEE International Symposium on Information Theory Proceedings, 293-297, 2011
252011
Equiangular tight frame fingerprinting codes
DG Mixon, C Quinn, N Kiyavash, M Fickus
2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011
152011
Combining human and machine intelligence to derive agents’ behavioral rules for groundwater irrigation
Y Hu, CJ Quinn, X Cai, NW Garfinkle
Advances in water resources 109, 29-40, 2017
102017
A generalized prediction framework for Granger causality
CJ Quinn, TP Coleman, N Kiyavash
2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS …, 2011
92011
Causal dependence tree approximations of joint distributions for multiple random processes
CJ Quinn, TP Coleman, N Kiyavash
arXiv preprint arXiv:1101.5108, 2011
62011
Robust directed tree approximations for networks of stochastic processes
CJ Quinn, J Etesami, N Kiyavash, TP Coleman
2013 IEEE International Symposium on Information Theory, 2254-2258, 2013
52013
Sparse approximations of directed information graphs
CJ Quinn, A Pinar, J Gao, L Su
2016 IEEE International Symposium on Information Theory (ISIT), 1735-1739, 2016
32016
Bounded degree approximations of stochastic networks
CJ Quinn, A Pinar, N Kiyavash
arXiv preprint arXiv:1506.04767, 2015
32015
Optimal bounded-degree approximations of joint distributions of networks of stochastic processes
CJ Quinn, A Pinar, N Kiyavash
2013 IEEE International Symposium on Information Theory, 2264-2268, 2013
32013
A minimal approach to causal inference on topologies with bounded indegree
C Quinn, N Kiyavash, T Coleman
2011 50th IEEE Conference on Decision and Control and European Control …, 2011
32011
Approximating discrete probability distributions with causal dependence trees
CJ Quinn, TP Coleman, N Kiyavash
2010 International Symposium On Information Theory & Its Applications, 100-105, 2010
32010
Visual Experience-Dependent Oscillations and Underlying Circuit Connectivity Changes Are Impaired in Fmr1 KO Mice
ST Kissinger, Q Wu, CJ Quinn, AK Anderson, A Pak, AA Chubykin
Cell reports 31 (1), 107486, 2020
22020
A Measure of Synergy, Redundancy, and Unique Information using Information Geometry
X Niu, CJ Quinn
2019 IEEE International Symposium on Information Theory (ISIT), 3127-3131, 2019
22019
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Articles 1–20