| A spatiotemporal epidemic model to quantify the effects of contact tracing, testing, and containment L Lorch, W Trouleau, S Tsirtsis, A Szanto, B Schölkopf, ... | 41 | 2020 |
| A kernel of truth: Determining rumor veracity on twitter by diffusion pattern alone N Rosenfeld, A Szanto, DC Parkes Proceedings of The Web Conference 2020, 1018-1028, 2020 | 27 | 2020 |
| Taint tracking for webassembly A Szanto, T Tamm, A Pagnoni arXiv preprint arXiv:1807.08349, 2018 | 15 | 2018 |
| Quantifying the effects of contact tracing, testing, and containment measures in the presence of infection hotspots L Lorch, H Kremer, W Trouleau, S Tsirtsis, A Szanto, B Schölkopf, ... arXiv preprint arXiv:2004.07641, 2020 | 12 | 2020 |
| A spatiotemporal epidemic model to quantify the effects of contact tracing L Lorch, W Trouleau, S Tsirtsis, A Szanto, B Schölkopf, ... Testing, and Containment, 2020 | 5 | 2020 |
| Quantifying the effects of contact tracing, testing, and containment L Lorch, H Kremer, W Trouleau, S Tsirtsis, A Szanto, B Schölkopf, ... | 4 | 2020 |
| A host of troubles: Re-identifying Airbnb hosts using public data A Szanto, N Mehta Technology Science. Oct, 2018 | 2 | 2018 |
| Defuse the News: Predicting Misinformation and Bias in News on Social Networks via Content-Blind Learning A Szanto | 1 | 2018 |
| A Kernel of Truth: Determining Rumor Veracity on Twitter by Diffusion Pattern Alone A Szanto, N Rosenfeld, DC Parkes arXiv, arXiv: 2002.00850, 2020 | | 2020 |
| The Skiplist-Based LSM Tree A Szanto arXiv preprint arXiv:1809.03261, 2018 | | 2018 |
| On the Flip Side: Identifying Counterexamples in Visual Question Answering G Grand, A Szanto, Y Kim, A Rush arXiv preprint arXiv:1806.00857, 2018 | | 2018 |
| Content-Blind Learning on Social Networks A Szanto Harvard University, 2017 | | 2017 |
| Modeling Large-Scale Collaboration on GitHub A Szanto, S Gehrmann | | |
David C. ParkesGeorge F. Colony Professor of Computer Science, Harvard UniversityVerified email at eecs.harvard.edu
