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, 17-44, 2011 | 302 | 2011 |
Directed information graphs CJ Quinn, N Kiyavash, TP Coleman IEEE Transactions on information theory 61 (12), 6887-6909, 2015 | 180 | 2015 |
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 | 92 | 2008 |
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 | 63 | 2016 |
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 | 43 | 2013 |
Fingerprinting with equiangular tight frames DG Mixon, CJ Quinn, N Kiyavash, M Fickus IEEE transactions on information theory 59 (3), 1855-1865, 2013 | 36 | 2013 |
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 | 33 | 2014 |
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), 2020 | 31 | 2020 |
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 | 31 | 2011 |
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 | 27 | 2017 |
A community-aware framework for social influence maximization AK Umrawal, CJ Quinn, V Aggarwal IEEE Transactions on Emerging Topics in Computational Intelligence 7 (4 …, 2023 | 17 | 2023 |
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 | 16 | 2019 |
Equiangular tight frame fingerprinting codes DG Mixon, C Quinn, N Kiyavash, M Fickus 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 16 | 2011 |
An explore-then-commit algorithm for submodular maximization under full-bandit feedback G Nie, M Agarwal, AK Umrawal, V Aggarwal, CJ Quinn Uncertainty in Artificial Intelligence, 1541-1551, 2022 | 15 | 2022 |
Stochastic Top K-Subset Bandits with Linear Space and Non-Linear Feedback with Applications to Social Influence Maximization M Agarwal, V Aggarwal, AK Umrawal, CJ Quinn ACM/IMS Transactions on Data Science (TDS) 2 (4), 1-39, 2022 | 10 | 2022 |
A generalized prediction framework for Granger causality CJ Quinn, TP Coleman, N Kiyavash 2011 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS …, 2011 | 10 | 2011 |
Taking it from the top: The growth and care of genres CJ Quinn Acts of reading: Exploring connections in pedagogy of Japanese, 38-60, 2003 | 10 | 2003 |
A framework for adapting offline algorithms to solve combinatorial multi-armed bandit problems with bandit feedback G Nie, YY Nadew, Y Zhu, V Aggarwal, CJ Quinn International Conference on Machine Learning, 26166-26198, 2023 | 9 | 2023 |
Dart: Adaptive accept reject algorithm for non-linear combinatorial bandits M Agarwal, V Aggarwal, AK Umrawal, C Quinn Proceedings of the AAAI Conference on Artificial Intelligence 35 (8), 6557-6565, 2021 | 8 | 2021 |
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 | 8 | 2010 |