Mohamed Akrout - Papers

For a complete and up-to-date list, please visit my Google Scholar profile.

Papers

Statistical Signal Processing

Unlabeled Compressed Sensing from Multiple Measurement Vectors, Akrout, M., Mezghani, A., and Bellili, F., IEEE Transactions on Signal Processing, 2025.
VAMP-based Kalman Filtering under non-Gaussian Process Noise, Gao, T. Akrout, M., Mezghani, A., and Bellili, F., IEEE Open Journal of Signal Processing, 2025.
Large-scale Unlabeled Compressed Sensing via Bilinear Matrix Recovery, Akrout, M., Mezghani, A., and Bellili, F., IEEE Asilomar, 2025 (to be published soon).
Extending Kalman Filters for non-Gaussian Process Noise Sources via Approximate Message Passing, Gao, T., Akrout, M., Bellili, F., and Mezghani, A., IEEE Asilomar, 2025 (to be published soon).
Vector Approximate Message Passing with i.i.d. Noise Priors, Akrout, M., Gao, T., Bellili, F., and Mezghani, A., IEEE Asilomar, 2024.
Distributed Vector Approximate Message Passing, Karuppasamy, M., Akrout, M., Bellili, F., and Mezghani, A., IEEE ICASSP, 2024.
BiG-VAMP: The Bilinear Generalized Vector Approximate Message Algorithm, Akrout, M., Housseini, A., Bellili, F., and Mezghani, A., IEEE Asilomar, 2022.

Deep Learning for Healthcare

Investigating the Performance of VisualDx on Common Dermatologic Conditions in Skin of Color, Cirone, K., Akrout, M., Simpson, R., and Lovegrove, F., SKIN: The Journal of Cutaneous Medicine, 2024.
Evaluation of vision LLMs GTP-4V and LLaVA for the Recognition of Features Characteristic of Melanoma, Akrout, M., Cirone, K., and Vender, R., Journal of Cutaneous Medicine and Surgery, 2024.
Diffusion-based Data Augmentation for Skin Disease Classification: Impact Across Original Medical Datasets to Fully Synthetic Images, Akrout, M., Gyepesi, B., Holló, P., Poór, A., Kincső, B., Solis, S., Cirone, K., Kawahara, J., Slade, D., Abid, L., Kovács, M., and Fazekas, I., MICCAI Deep Generative Models workshop, 2023.
Improving Skin Condition Classification with a Visual Symptom Checker Trained using Reinforcement Learning, Akrout, M., Farahmand, A.M., Jarmain, T., and Abid, L., MICCAI, 2019.
Deep Learning without Weight Transport, Akrout, M., Wilson, C., Humphreys, P., Lillicrap, T., and Tweed, D. B., Neural Information Processing Systems (NeurIPS), 2019.
Improving Skin Condition Classification with a Question Answering Model, Akrout, M., Farahmand, A., and Jarmain, T., Medical Imaging meets NeurIPS Workshop, 2018.

Combining Shannon and Maxwell Theories

Reincorporating Circuit Theory into Information Theory, Mezghani, A., Akrout, M., Castellanos, M. R., Bellili, F., Saab, S., Hochwald, B., Heath, R. W., and Nossek, J. A., IEEE BITS the Information Theory Magazine, 2023.
Physically Consistent Models for Intelligent Reflective Surface-assisted Communications under Mutual Coupling and Element Size Constraint, Akrout, M., Bellili, F., Mezghani, A., and Nossek, J. A., IEEE Asilomar Conference on Signals, Systems & Computers, 2023.
Bandwidth Gain: the Missing Gain of Massive MIMO, Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W., IEEE International Conference on Communications, 2023.
Super-Wideband Massive MIMO, Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W., IEEE JSAC special issue on Beyond Shannon Communications: A Paradigm Shift to Catalyze 6G, 2023.
Achievable Rate of Near-Field Communications Based on Physically Consistent Models, Akrout, M., Shyianov, V., Bellili, F., Mezghani, A., and Heath., R. W., IEEE Transactions on Wireless Communications, 2022.
Achievable Rate with Antenna Size Constraint: Shannon meets Chu and Bode, Akrout, M.*, Shyianov, V*., Bellili, F., Mezghani, A., and Heath., R. W. (* for joint first co-authorship), IEEE Transactions on Communications, 2021.

Data-driven Methods for Wireless Communications

Domain Generalization in Machine Learning Models for Wireless Communications: Concepts, State-of-the-Art, and Open Issues, Akrout, M., Feriani, A., Bellili, F., Mezghani, A., Hossain, E., IEEE Communications Surveys & Tutorials, 2023.
Continual Learning-Based MIMO Channel Estimation: A Benchmarking Study, Akrout, M., Feriani, A., Bellili, F., Mezghani, A., Hossain, E., IEEE International Conference on Communications, 2023.
Distributed Beamforming Techniques for Cell-Free Wireless Networks Using Deep Reinforcement Learning, Fredj, F., Al-Eryani, Y., Maghsudi, S., Akrout, M., and Hossain, E., IEEE Transactions on Cognitive Communications and Networking, 2022.
Multiple Access in Cell Free Networks: Outage Performance, Dynamic Clustering, and Deep Reinforcement Learning based Design, Al-Eryani, Y., Akrout, M., and Hossain, E., IEEE Journal on Selected Areas in Communications, 2021.
Antenna Clustering for Simultaneous Wireless Information and Power Transfer in a MIMO Full-duplex System: A Deep Reinforcement Learning-based Design, Al-Eryani, Y., Akrout, M., and Hossain, E., IEEE Transactions on Communications, 2021.

Other Areas of Deep Learning and Healthcare

A 35-Year Longitudinal Analysis of Dermatology Patient Behavior across Economic & Cultural Manifestations in Tunisia, and the Impact of Digital Tools, Akrout, M., Amdouni, H., Feriani, A., Kourda, M., Abid, L., MICCAI Workshop on Ethical and Philosophical Issues in Medical Imaging (EPIMI), 2022.
Dynamic Noises of Multi-agent Environments can Improve Generalization: Agent-based Models Meet Reinforcement Learning, Akrout, M., Feriani, A., McLeod, B., Gamification and Multiagent Solutions Workshop at ICLR 2022.
On the Adversarial Robustness of Neural Networks without Weight Transport, Akrout, M., Real Neurons & Hidden Units Workshop at NeurIPS 2019.
Benchmarking and Analyzing Deep Neural Network Training, Zhu, H., Akrout, M., Zheng, B., Pelegris, A., Jayarajan, A., Phanishayee, A., Schroeder, B. and Pekhimenko, G., IEEE International Symposium on Workload Characterization (IISWC), 2018.

Abid, L., Sanfiz, A. J., Lopez, A. R., Jarmain, E. T., Akrout, M., Challa, A., Kawahara, J. G., Solis-Reyes, S. A. System to collect and identify medical conditions from images and expert knowledge.