| Improving federated learning personalization via model agnostic meta learning Y Jiang, J Konečnı, K Rush, S Kannan arXiv preprint arXiv:1909.12488, 2019 | 669 | 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 | 419 | 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 | 382 | 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 | 320* | 2019 |
| Communication algorithms via deep learning H Kim, Y Jiang, R Rana, S Kannan, S Oh, P Viswanath arXiv preprint arXiv:1805.09317, 2018 | 275 | 2018 |
| Estimating mutual information for discrete-continuous mixtures W Gao, S Kannan, S Oh, P Viswanath Advances in neural information processing systems 30, 2017 | 208 | 2017 |
| 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 | 176* | 2020 |
| 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 | 173 | 2019 |
| 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 | 155 | 2017 |
| 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 | 149 | 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 | 125 | 2018 |
| 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 | 123 | 2020 |
| Themis: Fast, strong order-fairness in byzantine consensus M Kelkar, S Deb, S Long, A Juels, S Kannan Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications …, 2023 | 102 | 2023 |
| {DispersedLedger}:{High-Throughput} byzantine consensus on variable bandwidth networks L Yang, SJ Park, M Alizadeh, S Kannan, D Tse 19th USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2022 | 98 | 2022 |
| Coded merkle tree: Solving data availability attacks in blockchains M Yu, S Sahraei, S Li, S Avestimehr, S Kannan, P Viswanath International Conference on Financial Cryptography and Data Security, 114-134, 2020 | 96 | 2020 |
| 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 | 95 | 2020 |
| CCMI: Classifier based conditional mutual information estimation S Mukherjee, H Asnani, S Kannan Uncertainty in artificial intelligence, 1083-1093, 2020 | 93 | 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, 1-11, 2020 | 86 | 2020 |
| Perigee: Efficient peer-to-peer network design for blockchains Y Mao, S Deb, SB Venkatakrishnan, S Kannan, K Srinivasan Proceedings of the 39th Symposium on Principles of Distributed Computing …, 2020 | 78 | 2020 |
| BFT protocol forensics P Sheng, G Wang, K Nayak, S Kannan, P Viswanath Proceedings of the 2021 ACM SIGSAC conference on computer and communications …, 2021 | 75 | 2021 |
