| 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 | 311 | 2011 |
| Directed information graphs CJ Quinn, N Kiyavash, TP Coleman IEEE Transactions on information theory 61 (12), 6887-6909, 2015 | 184 | 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 | 93 | 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 | 64 | 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 | 41 | 2013 |
| Fingerprinting with equiangular tight frames DG Mixon, CJ Quinn, N Kiyavash, M Fickus IEEE transactions on information theory 59 (3), 1855-1865, 2013 | 39 | 2013 |
| 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 | 35 | 2020 |
| 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 | 33 | 2017 |
| 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 |
| 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 |
| 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 | 24 | 2022 |
| 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 | 21 | 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 | 20 | 2019 |
| Randomized greedy learning for non-monotone stochastic submodular maximization under full-bandit feedback F Fourati, V Aggarwal, C Quinn, MS Alouini International Conference on Artificial Intelligence and Statistics, 7455-7471, 2023 | 17 | 2023 |
| 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 | 16 | 2023 |
| 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 |
| Combinatorial stochastic-greedy bandit F Fourati, CJ Quinn, MS Alouini, V Aggarwal Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12052 …, 2024 | 11 | 2024 |
| A unified approach for maximizing continuous DR-submodular functions M Pedramfar, C Quinn, V Aggarwal Advances in Neural Information Processing Systems 36, 61103-61114, 2023 | 11 | 2023 |
| 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 | 11 | 2022 |
| 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 | 11 | 2021 |
