Applications of Machine Learning to Cognitive Radio Networks. - Charles Clancy; Joe Hecker; Erich P. Stuntebeck; Timothy J. O'Shea (IEEE Wirel. Commun., 2007)

Measuring smart jammer strategy efficacy over the air. - C. Carlson; Vieny Nguyen; Seth D. Hitefield; Timothy J. O'Shea; T. Charles Clancy (CNS, 2014)

Demonstrated LLC-layer attack and defense strategies for wireless communication systems. - Seth D. Hitefield; Vieny Nguyen; C. Carlson; Timothy J. O'Shea; T. Charles Clancy (CNS, 2014)

Radio transformer networks: Attention models for learning to synchronize in wireless systems. - Timothy J. O'Shea; Latha Pemula; Dhruv Batra; T. Charles Clancy (ACSSC, 2016)

Convolutional Radio Modulation Recognition Networks. - Timothy J. O'Shea; Johnathan Corgan; T. Charles Clancy (EANN, 2016)

End-to-end radio traffic sequence recognition with recurrent neural networks. - Timothy J. O'Shea; Seth D. Hitefield; Johnathan Corgan (GlobalSIP, 2016)

Learning to communicate: Channel auto-encoders, domain specific regularizers, and attention. - Timothy J. O'Shea; Kiran Karra; T. Charles Clancy (ISSPIT, 2016)

Unsupervised representation learning of structured radio communication signals. - Timothy J. O'Shea; Johnathan Corgan; T. Charles Clancy (SPLINE, 2016)

Convolutional Radio Modulation Recognition Networks. - Timothy J. O'Shea; Johnathan Corgan (CoRR, 2016)

Deep Reinforcement Learning Radio Control and Signal Detection with KeRLym, a Gym RL Agent. - Timothy J. O'Shea; T. Charles Clancy (CoRR, 2016)

Recurrent Neural Radio Anomaly Detection. - Timothy J. O'Shea; T. Charles Clancy; Robert W. McGwier (CoRR, 2016)

End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks. - Timothy J. O'Shea; Seth D. Hitefield; Johnathan Corgan (CoRR, 2016)

GNU Radio Signal Processing Models for Dynamic Multi-User Burst Modems. - Timothy J. O'Shea; Kiran Karra (CoRR, 2016)

A Modest Proposal for Open Market Risk Assessment to Solve the Cyber-Security Problem. - Timothy J. O'Shea; Adam Mondl; T. Charles Clancy (CoRR, 2016)

Semi-Supervised Radio Signal Identification. - Timothy J. O'Shea; Nathan E. West; Matthew Vondal; T. Charles Clancy (CoRR, 2016)

Learning robust general radio signal detection using computer vision methods. - Tim O'Shea 001; Tamoghna Roy; T. Charles Clancy (ACSSC, 2017)

Physical layer deep learning of encodings for the MIMO fading channel. - Timothy J. O'Shea; Tugba Erpek; T. Charles Clancy (Allerton, 2017)

Deep architectures for modulation recognition. - Nathan E. West; Timothy J. O'Shea (DySPAN, 2017)

Spectral detection and localization of radio events with learned convolutional neural features. - Timothy J. O'Shea; Tamoghna Roy; Tugba Erpek (EUSIPCO, 2017)

Learning approximate neural estimators for wireless channel state information. - Tim O'Shea 001; Kiran Karra; T. Charles Clancy (MLSP, 2017)

Deep Learning Based MIMO Communications. - Timothy J. O'Shea; Tugba Erpek; T. Charles Clancy (CoRR, 2017)

An Introduction to Machine Learning Communications Systems. - Timothy J. O'Shea; Jakob Hoydis (CoRR, 2017)

An Introduction to Deep Learning for the Physical Layer. - Timothy J. O'Shea; Jakob Hoydis (IEEE Trans. Cogn. Commun. Netw., 2017)

Learning from Data in Radio Algorithm Design. - Timothy J. O'Shea (2017)

Demonstrating Deep Learning Based Communications Systems Over the Air In Practice. - Timothy J. O'Shea; Tamoghna Roy; Nathan E. West; Benjamin C. Hilburn (DySPAN, 2018)

Physical Layer Communications System Design Over-the-Air Using Adversarial Networks. - Timothy J. O'Shea; Tamoghna Roy; Nathan E. West; Benjamin C. Hilburn (EUSIPCO, 2018)

Learning a Physical Layer Scheme for the MIMO Interference Channel. - Tugba Erpek; Timothy J. O'Shea; T. Charles Clancy (ICC, 2018)

Over-the-Air Deep Learning Based Radio Signal Classification. - Timothy J. O'Shea; Tamoghna Roy; T. Charles Clancy (IEEE J. Sel. Top. Signal Process., 2018)

Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks. - Timothy J. O'Shea; Tamoghna Roy; Nathan E. West (ICNC, 2019)

Generative Adversarial Radio Spectrum Networks. - Tamoghna Roy; Tim O'Shea 001; Nathan E. West (WiseML@WiSec, 2019)

Benchmarking End-to-end Learning of MIMO Physical-Layer Communication. - Jinxiang Song; Christian Häger; Jochen Schröder; Tim O'Shea 001; Henk Wymeersch (GLOBECOM, 2020)

Deep Learning for Wireless Communications. - Tugba Erpek; Timothy J. O'Shea; Yalin E. Sagduyu; Yi Shi 001; T. Charles Clancy (CoRR, 2020)

Special issue on advances and applications of artificial intelligence and machine learning for wireless communications. - H. Birkan Yilmaz 001; Chan-Byoung Chae; Yansha Deng; Tim O'Shea 001; Linglong Dai; Namyoon Lee; Jakob Hoydis (J. Commun. Networks, 2020)

Deep Learning for Wireless Communications. - Tugba Erpek; Timothy J. O'Shea; Yalin E. Sagduyu; Yi Shi 001; T. Charles Clancy (Development and Analysis of Deep Learning Architectures, 2020)

A Wideband Signal Recognition Dataset. - Nathan E. West; Timothy J. O'Shea; Tamoghna Roy (SPAWC, 2021)

IEEE TCCN Special Section Editorial: Machine Learning and Artificial Intelligence for the Physical Layer. - Chunxiao Jiang; Guoru Ding; Aly El Gamal; Andrea Zanella; Oliver Holland; Tim O'Shea 001 (IEEE Trans. Cogn. Commun. Netw., 2021)

SVD-Embedded Deep Autoencoder for MIMO Communications. - Xinliang Zhang; Mojtaba Vaezi; Timothy J. O'Shea (ICC, 2022)

Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. - Gopikrishna Rathinavel; Nikhil Muralidhar; Timothy J. O'Shea; Naren Ramakrishnan (ICDM, 2022)

Efficient Generative Wireless Anomaly Detection for Next Generation Networks. - Gopikrishna Rathinavel; Nikhil Muralidhar; Naren Ramakrishnan; Timothy J. O'Shea (MILCOM, 2022)

Scalable Wireless Anomaly Detection with Generative-LSTMs on RF Post-Detection Metadata. - Blake Barnes-Cook; Timothy J. O'Shea (WCNC, 2022)

Benchmarking and Interpreting End-to-End Learning of MIMO and Multi-User Communication. - Jinxiang Song; Christian Häger; Jochen Schröder; Timothy J. O'Shea; Erik Agrell; Henk Wymeersch (IEEE Trans. Wirel. Commun., 2022)

Deep Learning Based Uplink Multi-User SIMO Beamforming Design. - Cemil Vahapoglu; Timothy J. O'Shea; Tamoghna Roy; Sennur Ulukus (CoRR, 2023)

Data-Driven Design for IRS-Assisted Massive Multi-Modal Sensing in Industry 5.0. - Majumder Haider; Imtiaz Ahmed 001; Fadel Lashhab; Tim O'Shea 001; Danda B. Rawat; Mohammad Matin 002 (ICC Workshops, 2024)

Deep Learning Based Joint Multi-User MISO Power Allocation and Beamforming Design. - Cemil Vahapoglu; Timothy J. O'Shea; Tamoghna Roy; Sennur Ulukus (MILCOM, 2024)

Latent Space Correlation-Aware Autoencoder for Anomaly Detection in Skewed Data. - Padmaksha Roy; Himanshu Singhal; Timothy J. O'Shea; Ming Jin 002 (PAKDD (1), 2024)

How Critical is Site-Specific RAN Optimization? 5G Open-RAN Uplink Air Interface Performance Test and Optimization from Macro-Cell CIR Data. - Johnathan Corgan; Nitin Nair; Rajib Bhattacharjea; Wan Liu; Serhat Tadik; Tom Tsou; Timothy J. O'Shea (VTC Fall, 2024)

Transformer-Driven Neural Beamforming with Imperfect CSI in Urban Macro Wireless Channels. - Cemil Vahapoglu; Timothy J. O'Shea; Wan Liu; Tamoghna Roy; Sennur Ulukus (CoRR, 2025)

Digital Twin Enabled Site Specific Channel Precoding: Over the Air CIR Inference. - Majumder Haider; Imtiaz Ahmed 001; Zoheb Hassan; Timothy J. O'Shea; Lingjia Liu 001; Danda B. Rawat (IEEE Commun. Lett., 2025)