| Learning to communicate: Channel auto-encoders, domain specific regularizers, and attention TJ O'Shea, K Karra, TC Clancy 2016 IEEE International Symposium on Signal Processing and Information …, 2016 | 306 | 2016 |
| Learning approximate neural estimators for wireless channel state information T O'Shea, K Karra, TC Clancy 2017 IEEE 27th international workshop on machine learning for signal …, 2017 | 69 | 2017 |
| Learning approximate estimation networks for communication channel state information TJ O'shea, K Karra, TC Clancy US Patent 11,334,807, 2022 | 40 | 2022 |
| A data-driven nonparametric approach for probabilistic load-margin assessment considering wind power penetration Y Xu, L Mili, M Korkali, K Karra, Z Zheng, X Chen IEEE Transactions on Power Systems 35 (6), 4756-4768, 2020 | 33 | 2020 |
| The trojai software framework: An opensource tool for embedding trojans into deep learning models K Karra, C Ashcraft, N Fendley arXiv preprint arXiv:2003.07233, 2020 | 32 | 2020 |
| Poisoning deep reinforcement learning agents with in-distribution triggers C Ashcraft, K Karra arXiv preprint arXiv:2106.07798, 2021 | 28 | 2021 |
| Hybrid copula Bayesian networks K Karra, L Mili Conference on probabilistic graphical models, 240-251, 2016 | 16 | 2016 |
| Machine learning aided crop yield optimization C Ashcraft, K Karra arXiv preprint arXiv:2111.00963, 2021 | 14 | 2021 |
| Copula index for detecting dependence and monotonicity between stochastic signals K Karra, L Mili Information Sciences 485, 18-41, 2019 | 9 | 2019 |
| An Empirical Assessment of the Complexity and Realism of Synthetic Social Contact Networks* K Karra, S Swarup, J Graham 2018 IEEE International Conference on Big Data (Big Data), 3959-3967, 2018 | 8 | 2018 |
| Wireless Distributed Computing on the Android Platform K Karra Virginia Tech, 2012 | 7 | 2012 |
| Probabilistic load-margin assessment using vine copula and gaussian process emulation Y Xu, K Karra, L Mili, M Korkali, X Chen, Z Hu 2020 IEEE Power & Energy Society General Meeting (PESGM), 1-5, 2020 | 4 | 2020 |
| A copula statistic for measuring nonlinear dependence with application to feature selection in machine learning MB Hassine, L Mili, K Karra International journal of advanced computer science and application 8 (7 …, 2017 | 4 | 2017 |
| Speaker diarization using two-pass leave-one-out gaussian PLDA clustering of DNN embeddings K Karra, A McCree arXiv preprint arXiv:2104.02469, 2021 | 2 | 2021 |
| Smoothening block rewards: How much should miners pay for mining pools? A Cortes-Cubero, JP Madrigal-Cianci, K Karra, Z Zhang arXiv preprint arXiv:2309.02297, 2023 | 1 | 2023 |
| An Agent-Based Model Framework for Utility-Based Cryptoeconomies K Karra, T Mellan, M Silva, JP Madrigal-Cianci, AC Cortes, Z Zhang arXiv preprint arXiv:2307.15200, 2023 | 1 | 2023 |
| Modeling and Analysis of Non-Linear Dependencies using Copulas, with Applications to Machine Learning K Karra Virginia Tech, 2018 | 1 | 2018 |
| A Copula Statistic for Measuring Nonlinear Multivariate Dependence MB Hassine, L Mili, K Karra International Journal of Advanced Computer Science and Applications (IJACSA …, 2017 | 1 | 2017 |
| Adversarial Machine Learning and the Future Hybrid Battlespace C Ratto, M Pekala, N Fendley, N Drenkow, K Karra, C Ashcraft, C Costello, ... The Johns Hopkins University Applied Physics Laboratory, 0 | 1 | |
| Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics P Algikar, L Mili, K Karra, A Algikar, MB Hassine 2024 IEEE Power & Energy Society Innovative Smart Grid Technologies …, 2024 | | 2024 |
Tim O'SheaCTO/Founder, DeepSig在 vt.edu 的电子邮件经过验证
