| Improving federated learning personalization via model agnostic meta learning Y Jiang, J Konečný, K Rush, S Kannan arXiv preprint arXiv:1909.12488, 2019 | 405 | 2019 |
| Clustergan: Latent space clustering in generative adversarial networks S Mukherjee, H Asnani, E Lin, S Kannan Proceedings of the AAAI conference on artificial intelligence 33 (01), 4610-4617, 2019 | 296 | 2019 |
| Deceiving google's perspective api built for detecting toxic comments H Hosseini, S Kannan, B Zhang, R Poovendran arXiv preprint arXiv:1702.08138, 2017 | 281 | 2017 |
| Prism: Deconstructing the blockchain to approach physical limits V Bagaria, S Kannan, D Tse, G Fanti, P Viswanath Proceedings of the 2019 ACM SIGSAC Conference on Computer and Communications …, 2019 | 216* | 2019 |
| Communication algorithms via deep learning H Kim, Y Jiang, R Rana, S Kannan, S Oh, P Viswanath arXiv preprint arXiv:1805.09317, 2018 | 213 | 2018 |
| Estimating mutual information for discrete-continuous mixtures W Gao, S Kannan, S Oh, P Viswanath Advances in neural information processing systems 30, 2017 | 158 | 2017 |
| Blocking transferability of adversarial examples in black-box learning systems H Hosseini, Y Chen, S Kannan, B Zhang, R Poovendran arXiv preprint arXiv:1703.04318, 2017 | 130 | 2017 |
| Turbo autoencoder: Deep learning based channel codes for point-to-point communication channels Y Jiang, H Kim, H Asnani, S Kannan, S Oh, P Viswanath Advances in neural information processing systems 32, 2019 | 115 | 2019 |
| Inferring causal gene regulatory networks from coupled single-cell expression dynamics using scribe X Qiu, A Rahimzamani, L Wang, B Ren, Q Mao, T Durham, ... Cell systems 10 (3), 265-274. e11, 2020 | 107* | 2020 |
| Polyshard: Coded sharding achieves linearly scaling efficiency and security simultaneously S Li, M Yu, S Avestimehr, S Kannan, P Viswanath arXiv preprint arXiv:1809.10361, 2018 | 106 | 2018 |
| Deepcode: Feedback codes via deep learning H Kim, Y Jiang, S Kannan, S Oh, P Viswanath Advances in neural information processing systems 31, 2018 | 91 | 2018 |
| Learn codes: Inventing low-latency codes via recurrent neural networks Y Jiang, H Kim, H Asnani, S Kannan, S Oh, P Viswanath IEEE Journal on Selected Areas in Information Theory 1 (1), 207-216, 2020 | 76 | 2020 |
| Everything is a race and nakamoto always wins A Dembo, S Kannan, EN Tas, D Tse, P Viswanath, X Wang, O Zeitouni Proceedings of the 2020 ACM SIGSAC Conference on Computer and Communications …, 2020 | 75 | 2020 |
| CCMI: Classifier based conditional mutual information estimation S Mukherjee, H Asnani, S Kannan Uncertainty in artificial intelligence, 1083-1093, 2020 | 66 | 2020 |
| Coded merkle tree: Solving data availability attacks in blockchains M Yu, S Sahraei, S Li, S Avestimehr, S Kannan, P Viswanath Financial Cryptography and Data Security: 24th International Conference, FC …, 2020 | 62 | 2020 |
| A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis E Lin, S Mukherjee, S Kannan BMC bioinformatics 21 (1), 1-11, 2020 | 57 | 2020 |
| Deepturbo: Deep turbo decoder Y Jiang, S Kannan, H Kim, S Oh, H Asnani, P Viswanath 2019 IEEE 20th International Workshop on Signal Processing Advances in …, 2019 | 44 | 2019 |
| DMT of parallel-path and layered networks under the half-duplex constraint K Sreeram, S Birenjith, PV Kumar IEEE transactions on information theory 59 (6), 3875-3891, 2013 | 44* | 2013 |
| Mind: Model independent neural decoder Y Jiang, H Kim, H Asnani, S Kannan 2019 IEEE 20th International Workshop on Signal Processing Advances in …, 2019 | 43* | 2019 |
| Dmt of multihop networks: end points and computational tools K Sreeram, S Birenjith, PV Kumar IEEE transactions on information theory 58 (2), 804-819, 2012 | 40* | 2012 |
