| Denotational cost semantics for functional languages with inductive types N Danner, DR Licata, R Ramyaa Proceedings of the 20th ACM SIGPLAN International Conference on Functional …, 2015 | 72 | 2015 |
| Mind the gap: On bridging the semantic gap between machine learning and malware analysis MR Smith, NT Johnson, JB Ingram, AJ Carbajal, BI Haus, E Domschot, ... Proceedings of the 13th ACM Workshop on Artificial Intelligence and Security …, 2020 | 34 | 2020 |
| Biologically inspired sleep algorithm for artificial neural networks GP Krishnan, T Tadros, R Ramyaa, M Bazhenov arXiv preprint arXiv:1908.02240, 2019 | 26 | 2019 |
| Phenotyping women based on dietary macronutrients, physical activity, and body weight using machine learning tools R Ramyaa, O Hosseini, GP Krishnan, S Krishnan Nutrients 11 (7), 1681, 2019 | 26 | 2019 |
| Prediction of frost for fruit protection using artificial neural networks A Jain, RW McClendon, G Hoogenboom, R Ramyaa American Society of Agricultural Engineers, St. Joseph, MI, ASAE Paper, 03-3075, 2003 | 25 | 2003 |
| Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks T Tadros, G Krishnan, R Ramyaa, M Bazhenov International Conference on Learning Representations, 2019 | 21 | 2019 |
| Sleep-like unsupervised replay reduces catastrophic forgetting in artificial neural networks T Tadros, GP Krishnan, R Ramyaa, M Bazhenov Nature communications 13 (1), 7742, 2022 | 17 | 2022 |
| Ramified corecurrence and logspace R Ramyaa, D Leivant Electronic Notes in Theoretical Computer Science 276, 247-261, 2011 | 14 | 2011 |
| Validating distance decay through agent based modeling A Verma, R Ramyaa, S Marru Security Informatics 2, 1-11, 2013 | 12 | 2013 |
| Rationalizing police patrol beats using Voronoi Tessellations A Verma, R Ramyaa, S Marru, Y Fan, R Singh 2010 IEEE International Conference on Intelligence and Security Informatics …, 2010 | 12 | 2010 |
| Biologically inspired sleep algorithm for reducing catastrophic forgetting in neural networks T Tadros, G Krishnan, R Ramyaa, M Bazhenov Proceedings of the AAAI Conference on Artificial Intelligence 34 (10), 13933 …, 2020 | 8 | 2020 |
| Mind the gap: On bridging the semantic gap between machine learning and information security MR Smith, NT Johnson, JB Ingram, AJ Carbajal, R Ramyaa, E Domschot, ... arXiv preprint arXiv:2005.01800, 2020 | 6 | 2020 |
| Pure pointer programs and tree isomorphism M Hofmann, R Ramyaa, U Schöpp International Conference on Foundations of Software Science and …, 2013 | 6 | 2013 |
| Learning with distributional inverters E Binnendyk, M Carmosino, A Kolokolova, R Ramyaa, M Sabin International Conference on Algorithmic Learning Theory, 90-106, 2022 | 5 | 2022 |
| When two heads are better than one: nutritional epidemiology meets machine learning S Krishnan, R Ramyaa The American Journal of Clinical Nutrition 111 (6), 1124-1126, 2020 | 5 | 2020 |
| Implicit complexity for coinductive data: a characterization of corecurrence D Leivant, R Ramyaa arXiv preprint arXiv:1201.1119, 2012 | 5 | 2012 |
| Using educational game for engaging students in learning foundational concepts of propositional logic A Towler, D Aranda, R Ramyaa, R Kuo 2020 IEEE 20th International Conference on Advanced Learning Technologies …, 2020 | 4 | 2020 |
| Feasible functions over co-inductive data R Ramyaa, D Leivant International Workshop on Logic, Language, Information, and Computation, 191-203, 2010 | 4 | 2010 |
| Learning Rules with Stratified Negation in Differentiable ILP. GP Krishnan, F Maier, R Ramyaa Advances in Programming Languages and Neurosymbolic Systems Workshop, 2021 | 3 | 2021 |
| The computational contents of ramified corecurrence D Leivant, R Ramyaa Foundations of Software Science and Computation Structures: 18th …, 2015 | 3 | 2015 |
