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2020 – today
- 2024
[j17]Nikita Mehandru
, Brenda Y. Miao, Eduardo Rodriguez Almaraz, Madhumita Sushil, Atul J. Butte, Ahmed M. Alaa:
Evaluating large language models as agents in the clinic. npj Digit. Medicine 7(1) (2024)- [c35]Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed M. Alaa:
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists. ICLR 2024 - [c34]Ilker Demirel, Ahmed M. Alaa, Anthony Philippakis, David A. Sontag:
Prediction-powered Generalization of Causal Inferences. ICML 2024 - [i55]Lars van der Laan, Ahmed M. Alaa:
Self-Consistent Conformal Prediction. CoRR abs/2402.07307 (2024) - [i54]Keying Kuang, Frances Dean, Jack B. Jedlicki, David Ouyang, Anthony Philippakis, David A. Sontag, Ahmed M. Alaa:
Non-Invasive Medical Digital Twins using Physics-Informed Self-Supervised Learning. CoRR abs/2403.00177 (2024) - [i53]Shenghuan Sun, Gregory M. Goldgof, Alexander Schubert, Zhiqing Sun, Thomas Hartvigsen, Atul J. Butte, Ahmed M. Alaa:
Dr-LLaVA: Visual Instruction Tuning with Symbolic Clinical Grounding. CoRR abs/2405.19567 (2024) - [i52]Ilker Demirel, Ahmed M. Alaa, Anthony Philippakis, David A. Sontag:
Prediction-powered Generalization of Causal Inferences. CoRR abs/2406.02873 (2024) - [i51]Christina X. Ji, Ahmed M. Alaa, David A. Sontag:
Seq-to-Final: A Benchmark for Tuning from Sequential Distributions to a Final Time Point. CoRR abs/2407.09642 (2024) - 2023
- [c33]Ahmed M. Alaa, Zeshan M. Hussain, David A. Sontag:
Conformalized Unconditional Quantile Regression. AISTATS 2023: 10690-10702 - [c32]Christina X. Ji, Ahmed M. Alaa, David A. Sontag:
Large-Scale Study of Temporal Shift in Health Insurance Claims. CHIL 2023: 243-278 - [c31]Ahmed M. Alaa, Zaid Ahmad, Mark J. van der Laan:
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects. NeurIPS 2023 - [c30]Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed M. Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala:
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. NeurIPS 2023 - [c29]Shenghuan Sun, Gregory M. Goldgof, Atul J. Butte, Ahmed M. Alaa:
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback. NeurIPS 2023 - [i50]Ahmed M. Alaa, Zeshan M. Hussain, David A. Sontag:
Conformalized Unconditional Quantile Regression. CoRR abs/2304.01426 (2023) - [i49]Christina X. Ji, Ahmed M. Alaa, David A. Sontag:
Large-Scale Study of Temporal Shift in Health Insurance Claims. CoRR abs/2305.05087 (2023) - [i48]Ali Shirali, Alexander Schubert, Ahmed M. Alaa:
Pruning the Way to Reliable Policies: A Multi-Objective Deep Q-Learning Approach to Critical Care. CoRR abs/2306.08044 (2023) - [i47]Shenghuan Sun, Gregory M. Goldgof, Atul J. Butte, Ahmed M. Alaa:
Aligning Synthetic Medical Images with Clinical Knowledge using Human Feedback. CoRR abs/2306.12438 (2023) - [i46]Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed M. Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala:
DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology. CoRR abs/2306.13384 (2023) - [i45]Nikita Mehandru, Brenda Y. Miao, Eduardo Rodriguez Almaraz, Madhumita Sushil, Atul J. Butte, Ahmed M. Alaa:
Large Language Models as Agents in the Clinic. CoRR abs/2309.10895 (2023) - [i44]Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed M. Alaa:
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists. CoRR abs/2310.00390 (2023) - [i43]Shiladitya Dutta, Hongbo Wei, Lars van der Laan, Ahmed M. Alaa:
Estimating Uncertainty in Multimodal Foundation Models using Public Internet Data. CoRR abs/2310.09926 (2023) - [i42]Ayush Jain, Marie-Laure Charpignon, Irene Y. Chen, Anthony Philippakis, Ahmed M. Alaa:
Generating Drug Repurposing Hypotheses through the Combination of Disease-Specific Hypergraphs. CoRR abs/2311.09596 (2023) - [i41]Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt D. Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson:
DMLR: Data-centric Machine Learning Research - Past, Present and Future. CoRR abs/2311.13028 (2023) - 2022
- [j16]Ahmed M. Alaa:
Mining for informative signals in biological sequences. Nat. Mach. Intell. 4(8): 665-666 (2022) - [c28]Ahmed M. Alaa, Boris van Breugel, Evgeny S. Saveliev, Mihaela van der Schaar:
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models. ICML 2022: 290-306 - [c27]Antonio Parziale, Monica Agrawal, Shengpu Tang, Kristen Severson, Luis Oala, Adarsh Subbaswamy, Sayantan Kumar, Elora D. M. Schörverth, Stefan Hegselmann, Helen Zhou, Ghada Zamzmi, Purity Mugambi, Elena Sizikova, Girmaw Abebe Tadesse, Yuyin Zhou, Taylor W. Killian, Haoran Zhang, Fahad Kamran, Andrea Hobby, Mars Huang, Ahmed M. Alaa, Harvineet Singh, Irene Y. Chen, Shalmali Joshi:
Machine Learning for Health (ML4H) 2022. ML4H@NeurIPS 2022: 1-11 - [c26]Ahmed M. Alaa, Anthony Philippakis, David A. Sontag:
ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography. NeurIPS 2022 - 2021
- [j15]Mihaela van der Schaar, Ahmed M. Alaa, R. Andres Floto, Alexander Gimson, Stefan Scholtes, Angela M. Wood, Eoin F. McKinney, Daniel Jarrett, Pietro Lió, Ari Ercole:
How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. Mach. Learn. 110(1): 1-14 (2021) - [j14]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
CPAS: the UK's national machine learning-based hospital capacity planning system for COVID-19. Mach. Learn. 110(1): 15-35 (2021) - [j13]Ahmed M. Alaa, Deepti Gurdasani, Adrian L. Harris, Jem Rashbass, Mihaela van der Schaar:
Machine learning to guide the use of adjuvant therapies for breast cancer. Nat. Mach. Intell. 3(8): 716-726 (2021) - [c25]Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar:
Learning Matching Representations for Individualized Organ Transplantation Allocation. AISTATS 2021: 2134-2142 - [c24]Ahmed M. Alaa, Alex James Chan, Mihaela van der Schaar:
Generative Time-series Modeling with Fourier Flows. ICLR 2021 - [c23]Jeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar:
Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis. ICML 2021: 792-802 - [c22]Kamile Stankeviciute, Ahmed M. Alaa, Mihaela van der Schaar:
Conformal Time-series Forecasting. NeurIPS 2021: 6216-6228 - [i40]Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar:
Learning Matching Representations for Individualized Organ Transplantation Allocation. CoRR abs/2101.11769 (2021) - [i39]Ahmed M. Alaa, Boris van Breugel, Evgeny Saveliev, Mihaela van der Schaar:
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models. CoRR abs/2102.08921 (2021) - 2020
- [c21]Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass:
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. AISTATS 2020: 3295-3305 - [c20]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating counterfactual treatment outcomes over time through adversarially balanced representations. ICLR 2020 - [c19]Ahmed M. Alaa, Mihaela van der Schaar:
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions. ICML 2020: 165-174 - [c18]Ahmed M. Alaa, Mihaela van der Schaar:
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions. ICML 2020: 175-190 - [c17]Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar:
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. ICML 2020: 884-895 - [c16]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. ICML 2020: 1392-1402 - [c15]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes. NeurIPS 2020 - [i38]Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Jem Rashbass, Mihaela van der Schaar:
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. CoRR abs/2001.02585 (2020) - [i37]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations. CoRR abs/2002.04083 (2020) - [i36]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
When to Lift the Lockdown? Global COVID-19 Scenario Planning and Policy Effects using Compartmental Gaussian Processes. CoRR abs/2005.08837 (2020) - [i35]Ahmed M. Alaa, Mihaela van der Schaar:
Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions. CoRR abs/2006.13707 (2020) - [i34]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. CoRR abs/2006.14988 (2020) - [i33]Ahmed M. Alaa, Mihaela van der Schaar:
Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions. CoRR abs/2007.13481 (2020) - [i32]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19. CoRR abs/2007.13825 (2020)
2010 – 2019
- 2019
- [c14]Changhee Lee, William R. Zame, Ahmed M. Alaa, Mihaela van der Schaar:
Temporal Quilting for Survival Analysis. AISTATS 2019: 596-605 - [c13]Ahmed M. Alaa, Mihaela van der Schaar:
Validating Causal Inference Models via Influence Functions. ICML 2019: 191-201 - [c12]Ahmed M. Alaa, Mihaela van der Schaar:
Demystifying Black-box Models with Symbolic Metamodels. NeurIPS 2019: 11301-11311 - [c11]Ahmed M. Alaa, Mihaela van der Schaar:
Attentive State-Space Modeling of Disease Progression. NeurIPS 2019: 11334-11344 - [i31]Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar:
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. CoRR abs/1902.00450 (2019) - [i30]Yao Zhang, James Jordon, Ahmed M. Alaa, Mihaela van der Schaar:
Lifelong Bayesian Optimization. CoRR abs/1905.12280 (2019) - 2018
- [j12]Ahmed M. Alaa, Mihaela van der Schaar:
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference. J. Mach. Learn. Res. 19: 4:1-4:62 (2018) - [j11]Ahmed M. Alaa, Mihaela van der Schaar:
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms. IEEE J. Sel. Top. Signal Process. 12(5): 1031-1046 (2018) - [j10]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Personalized Risk Scoring for Critical Care Prognosis Using Mixtures of Gaussian Processes. IEEE Trans. Biomed. Eng. 65(1): 207-218 (2018) - [j9]Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar:
A Micro-Foundation of Social Capital in Evolving Social Networks. IEEE Trans. Netw. Sci. Eng. 5(1): 14-31 (2018) - [j8]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Opportunistic Beamforming Using Dumb Basis Patterns in Cognitive Multiple Access Channels. IEEE Trans. Veh. Technol. 67(2): 1417-1427 (2018) - [c10]Ahmed M. Alaa, Mihaela van der Schaar:
Limits of Estimating Heterogeneous Treatment Effects: Guidelines for Practical Algorithm Design. ICML 2018: 129-138 - [c9]Ahmed M. Alaa, Mihaela van der Schaar:
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning. ICML 2018: 139-148 - [i29]Ahmed M. Alaa, Mihaela van der Schaar:
AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning. CoRR abs/1802.07207 (2018) - [i28]Ahmed M. Alaa, Mihaela van der Schaar:
Forecasting Individualized Disease Trajectories using Interpretable Deep Learning. CoRR abs/1810.10489 (2018) - 2017
- [j7]Ahmed M. Alaa, Mahmoud H. Ismail:
Achievable Degrees of Freedom of the K-User SISO Interference Channel With Blind Interference Alignment Using Staggered Antenna Switching. IEEE Trans. Veh. Technol. 66(3): 2825-2829 (2017) - [c8]Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar:
Personalized Donor-Recipient Matching for Organ Transplantation. AAAI 2017: 1647-1654 - [c7]Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar:
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis. ICML 2017: 60-69 - [i27]Ahmed M. Alaa, Mihaela van der Schaar:
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes. CoRR abs/1704.02801 (2017) - [i26]Jinsung Yoon, William R. Zame, Amitava Banerjee, Martin Cadeiras, Ahmed M. Alaa, Mihaela van der Schaar:
Personalized Survival Predictions for Cardiac Transplantation via Trees of Predictors. CoRR abs/1704.03458 (2017) - [i25]Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar:
Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis. CoRR abs/1705.05267 (2017) - [i24]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Individualized Risk Prognosis for Critical Care Patients: A Multi-task Gaussian Process Model. CoRR abs/1705.07674 (2017) - [i23]Ahmed M. Alaa, Michael Weisz, Mihaela van der Schaar:
Deep Counterfactual Networks with Propensity-Dropout. CoRR abs/1706.05966 (2017) - [i22]Ahmed M. Alaa, Mihaela van der Schaar:
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms. CoRR abs/1712.08914 (2017) - 2016
- [j6]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Spectrum sensing via reconfigurable antennas: fundamental limits and potential gains. Telecommun. Syst. 62(3): 581-602 (2016) - [j5]Ahmed M. Alaa, Kyeong H. Moon, William Hsu, Mihaela van der Schaar:
ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening. IEEE Trans. Multim. 18(10): 1942-1955 (2016) - [j4]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Random Aerial Beamforming for Underlay Cognitive Radio With Exposed Secondary Users. IEEE Trans. Veh. Technol. 65(7): 5364-5383 (2016) - [j3]Ahmed M. Alaa, Yasmine A. Fahmy:
Defeating the Eavesdropper: On the Achievable Secrecy Capacity Using Reconfigurable Antennas. Wirel. Pers. Commun. 91(2): 729-738 (2016) - [c6]Jinsung Yoon, Ahmed M. Alaa, Scott Hu, Mihaela van der Schaar:
ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission. ICML 2016: 1680-1689 - [c5]Ahmed M. Alaa, Mihaela van der Schaar:
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition. NIPS 2016: 2910-2918 - [i21]Ahmed M. Alaa, Kyeong H. Moon, William Hsu, Mihaela van der Schaar:
ConfidentCare: A Clinical Decision Support System for Personalized Breast Cancer Screening. CoRR abs/1602.00374 (2016) - [i20]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Personalized Risk Scoring for Critical Care Patients using Mixtures of Gaussian Process Experts. CoRR abs/1605.00959 (2016) - [i19]Ahmed M. Alaa, Mihaela van der Schaar:
Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition. CoRR abs/1610.07505 (2016) - [i18]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
Personalized Risk Scoring for Critical Care Prognosis using Mixtures of Gaussian Processes. CoRR abs/1610.08853 (2016) - [i17]Jinsung Yoon, Ahmed M. Alaa, Martin Cadeiras, Mihaela van der Schaar:
Personalized Donor-Recipient Matching for Organ Transplantation. CoRR abs/1611.03934 (2016) - [i16]Ahmed M. Alaa, Jinsung Yoon, Scott Hu, Mihaela van der Schaar:
A Semi-Markov Switching Linear Gaussian Model for Censored Physiological Data. CoRR abs/1611.05146 (2016) - [i15]Ahmed M. Alaa, Mihaela van der Schaar:
A Hidden Absorbing Semi-Markov Model for Informatively Censored Temporal Data: Learning and Inference. CoRR abs/1612.06007 (2016) - 2015
- [j2]Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar:
Self-Organizing Networks of Information Gathering Cognitive Agents. IEEE Trans. Cogn. Commun. Netw. 1(1): 100-112 (2015) - [j1]Ahmed M. Alaa, Omar A. Nasr:
Globally Optimal Cooperation in Dense Cognitive Radio Networks. Wirel. Pers. Commun. 84(2): 885-899 (2015) - [c4]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Opportunistic spectrum sharing using dumb basis patterns: The Line-of-Sight interference scenario. ICNC 2015: 445-450 - [i14]Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar:
Self-organizing Networks of Information Gathering Cognitive Agents. CoRR abs/1503.04768 (2015) - [i13]Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar:
Evolution of Social Networks: A Microfounded Model. CoRR abs/1508.00205 (2015) - [i12]Ahmed M. Alaa, Kartik Ahuja, Mihaela van der Schaar:
A Micro-foundation of Social Capital in Evolving Social Networks. CoRR abs/1511.02429 (2015) - 2014
- [c3]Ahmed M. Alaa, Omar A. Nasr:
A globally optimal Neyman-Pearson test for hard decisions fusion in cooperative spectrum sensing. ICNC 2014: 605-610 - [c2]Mustafa A. Kishk, Ahmed M. Alaa:
On the capacity of the underwater acoustic channel with dominant noise sources. ISTT 2014: 183-187 - [c1]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Spectrum sensing via reconfigurable antennas: Is cooperation of secondary users indispensable? WCNC 2014: 966-971 - [i11]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Spectrum Sensing Via Reconfigurable Antennas: Is Cooperation of Secondary Users Indispensable? CoRR abs/1401.7772 (2014) - [i10]Ahmed M. Alaa:
Defeating the Eavesdropper: On the Achievable Secrecy Capacity using Reconfigurable Antennas. CoRR abs/1402.0993 (2014) - [i9]Ahmed M. Alaa, Omar A. Nasr:
Globally Optimal Cooperation in Dense Cognitive Radio Networks. CoRR abs/1402.6243 (2014) - [i8]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Spectrum Sensing Via Reconfigurable Antennas: Fundamental Limits and Potential Gains. CoRR abs/1403.0930 (2014) - [i7]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Opportunistic Spectrum Sharing using Dumb Basis Patterns: The Line-of-Sight Interference Scenario. CoRR abs/1403.7532 (2014) - [i6]Mustafa A. Kishk, Ahmed M. Alaa:
On the Capacity of the Underwater Acoustic Channel with Dominant Noise Sources. CoRR abs/1404.6737 (2014) - [i5]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Random Aerial Beamforming for Underlay Cognitive Radio with Exposed Secondary Users. CoRR abs/1406.1724 (2014) - [i4]Ahmed M. Alaa:
Band-Sweeping M-ary PSK (BS-M-PSK) Modulation and Transceiver Design. CoRR abs/1406.4162 (2014) - [i3]Ahmed M. Alaa, Mahmoud H. Ismail, Hazim Tawfik:
Opportunistic Beamforming using Dumb Basis Patterns in Multiple Access Cognitive Channels. CoRR abs/1407.1383 (2014) - [i2]Ahmed M. Alaa:
Stable Throughput Region of Cognitive-Relay Networks with Imperfect Sensing and Finite Relaying Buffer. CoRR abs/1408.1025 (2014) - [i1]Ahmed M. Alaa, Mahmoud H. Ismail:
Achievable Degrees-of-Freedom Through Blind Interference Alignment using Staggered Antenna Switching for the K-user SISO Interference Channel. CoRR abs/1408.6427 (2014)
Coauthor Index
[i41] [c28] [j15] [j14] [j13] [c25] [c24] [c23] [c22] [i40] [i39] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [i38] [i37] [i36] [i35] [i34] [i33] [i32] [c14] [c13] [c12] [c11] [i31] [i30] [j12] [j11] [j10] [j9] [c10] [c9] [i29] [i28] [c8] [c7] [i27] [i26] [i25] [i24] [i23] [i22] [j5] [c6] [c5] [i21] [i20] [i19] [i18] [i17] [i16] [i15] [j2] [i14] [i13] [i12]
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