Timothy J. O'Shea

Proceedings of the IEEE Wireless Communications and Networking Conference, 2022

Efficient Generative Wireless Anomaly Detection for Next Generation Networks.

[BibT_eX]

[DOI]

Gopikrishna Rathinavel

Nikhil Muralidhar

Naren Ramakrishnan

Proceedings of the IEEE Military Communications Conference, 2022

Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback.

[BibT_eX]

[DOI]

Gopikrishna Rathinavel

Nikhil Muralidhar

Naren Ramakrishnan

Proceedings of the IEEE International Conference on Data Mining, 2022

SVD-Embedded Deep Autoencoder for MIMO Communications.

[BibT_eX]

[DOI]

Xinliang Zhang

Mojtaba Vaezi

Proceedings of the IEEE International Conference on Communications, 2022

2021

IEEE TCCN Special Section Editorial: Machine Learning and Artificial Intelligence for the Physical Layer.

[BibT_eX]

[DOI]

IEEE Trans. Cogn. Commun. Netw., 2021

A Wideband Signal Recognition Dataset.

[BibT_eX]

[DOI]

Proceedings of the 22nd IEEE International Workshop on Signal Processing Advances in Wireless Communications, 2021

2020

Deep Learning for Wireless Communications.

[BibT_eX]

[DOI]

Proceedings of the Development and Analysis of Deep Learning Architectures, 2020

Special issue on advances and applications of artificial intelligence and machine learning for wireless communications.

[BibT_eX]

[DOI]

J. Commun. Networks, 2020

Deep Learning for Wireless Communications.

[BibT_eX]

[DOI]

CoRR, 2020

Benchmarking End-to-end Learning of MIMO Physical-Layer Communication.

[BibT_eX]

[DOI]

Proceedings of the IEEE Global Communications Conference, 2020

2019

Generative Adversarial Radio Spectrum Networks.

[BibT_eX]

[DOI]

Tim O'Shea

Proceedings of the ACM Workshop on Wireless Security and Machine Learning, 2019

Approximating the Void: Learning Stochastic Channel Models from Observation with Variational Generative Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Computing, Networking and Communications, 2019

2018

Over-the-Air Deep Learning Based Radio Signal Classification.

[BibT_eX]

[DOI]

IEEE J. Sel. Top. Signal Process., 2018

Learning a Physical Layer Scheme for the MIMO Interference Channel.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Communications, 2018

Physical Layer Communications System Design Over-the-Air Using Adversarial Networks.

[BibT_eX]

[DOI]

Proceedings of the 26th European Signal Processing Conference, 2018

Demonstrating Deep Learning Based Communications Systems Over the Air In Practice.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Symposium on Dynamic Spectrum Access Networks, 2018

2017

Learning from Data in Radio Algorithm Design.

[BibT_eX]

[DOI]

PhD thesis, 2017

An Introduction to Deep Learning for the Physical Layer.

[BibT_eX]

[DOI]

Jakob Hoydis

IEEE Trans. Cogn. Commun. Netw., 2017

An Introduction to Machine Learning Communications Systems.

[BibT_eX]

[DOI]

Jakob Hoydis

CoRR, 2017

Deep Learning Based MIMO Communications.

[BibT_eX]

[DOI]

CoRR, 2017

Learning approximate neural estimators for wireless channel state information.

[BibT_eX]

[DOI]

Tim O'Shea

Kiran Karra

Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017

Spectral detection and localization of radio events with learned convolutional neural features.

[BibT_eX]

[DOI]

Proceedings of the 25th European Signal Processing Conference, 2017

Deep architectures for modulation recognition.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Symposium on Dynamic Spectrum Access Networks, 2017

Physical layer deep learning of encodings for the MIMO fading channel.

[BibT_eX]

[DOI]

Proceedings of the 55th Annual Allerton Conference on Communication, 2017

Learning robust general radio signal detection using computer vision methods.

[BibT_eX]

[DOI]

Tim O'Shea

Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016

Semi-Supervised Radio Signal Identification.

[BibT_eX]

[DOI]

CoRR, 2016

A Modest Proposal for Open Market Risk Assessment to Solve the Cyber-Security Problem.

[BibT_eX]

[DOI]

Adam Mondl

CoRR, 2016

GNU Radio Signal Processing Models for Dynamic Multi-User Burst Modems.

[BibT_eX]

[DOI]

Kiran Karra

CoRR, 2016

End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks.

[BibT_eX]

[DOI]

Seth D. Hitefield

CoRR, 2016

Recurrent Neural Radio Anomaly Detection.

[BibT_eX]

[DOI]

Robert W. McGwier

CoRR, 2016

Deep Reinforcement Learning Radio Control and Signal Detection with KeRLym, a Gym RL Agent.

[BibT_eX]

[DOI]

CoRR, 2016

Convolutional Radio Modulation Recognition Networks.

[BibT_eX]

[DOI]

CoRR, 2016

Unsupervised representation learning of structured radio communication signals.

[BibT_eX]

[DOI]

Proceedings of the First International Workshop on Sensing, 2016

Learning to communicate: Channel auto-encoders, domain specific regularizers, and attention.

[BibT_eX]

[DOI]

Kiran Karra

Proceedings of the 2016 IEEE International Symposium on Signal Processing and Information Technology, 2016

End-to-end radio traffic sequence recognition with recurrent neural networks.

[BibT_eX]

[DOI]

Seth D. Hitefield

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Convolutional Radio Modulation Recognition Networks.

[BibT_eX]

[DOI]