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Kiran Karra
Kiran Karra
Protocol Labs
在 protocol.ai 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
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
2642016
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
642017
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
262020
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
242020
Poisoning deep reinforcement learning agents with in-distribution triggers
C Ashcraft, K Karra
arXiv preprint arXiv:2106.07798, 2021
192021
Hybrid copula Bayesian networks
K Karra, L Mili
Conference on probabilistic graphical models, 240-251, 2016
162016
Learning approximate estimation networks for communication channel state information
TJ O'shea, K Karra, TC Clancy
US Patent 11,334,807, 2022
102022
Machine learning aided crop yield optimization
C Ashcraft, K Karra
arXiv preprint arXiv:2111.00963, 2021
102021
Copula index for detecting dependence and monotonicity between stochastic signals
K Karra, L Mili
Information Sciences 485, 18-41, 2019
92019
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
72018
Wireless Distributed Computing on the Android Platform
K Karra
Virginia Tech, 2012
72012
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
32020
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 Applications 8 (7), 2017
32017
Speaker Diarization using Two-pass Leave-One-Out Gaussian PLDA Clustering of DNN Embeddings
K Karra, A McCree
arXiv preprint arXiv:2104.02469, 2021
22021
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
12023
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
12023
Adversarial Machine Learning and the Future Hybrid Battlespace
C Ratto, M Pekala, N Fendley, N Drenkow, K Karra, C Ashcraft, C Costello, ...
1
Kullback-Leibler Divergence-Guided Copula Statistics-Based Blind Source Separation of Dependent Signals
P Algikar, L Mili, K Karra, MB Hassine
arXiv preprint arXiv:2309.07814, 2023
2023
Quantifying Non-linear Dependencies in Blind Source Separation of Power System Signals using Copula Statistics
P Algikar, L Mili, K Karra, A Algikar, M Ben Hassine
arXiv e-prints, arXiv: 2309.07814, 2023
2023
Learning approximate estimation networks for communication channel state information
TJ O'shea, K Karra, TC Clancy
US Patent 11,699,086, 2023
2023
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